INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD
AND PROGRAM
BACKGROUND
5 [0001] Modes pertaining to the present invention relate to an information
processing system, an information processing method and a program.
[0002] In recent years, a system is being considered for performing wide-range
monitoring by using videos (or images) captured with a plurality of cameras. For
instance, Patent Document 1 discloses a device capable of appropriately tracking
10 (monitoring) a person across cameras by using topology information between
cameras. This device comprises a function of estimating the existence of topology
between cameras by creating a histogram relating to a pair of a position (Out point)
where the person disappeared from the camera view, and a position (In point) where
the person subsequently appears in the camera view, and a function of displaying,
15 through highlighting, an image of a camera in which the probability that the person will
subsequently appear is high according to the topology.
[0003] Patent Document 1: Patent Publication JP-A-2008-219570
SUMMARY
20 [0004] Nevertheless, with the method described in Patent Document 1, unless
the disappearance position of the person to be tracked is identified, it is not possible to
identify the video camera where that person will subsequently appear. Thus, for
instance, when the imaging positions of two video cameras are extremely close, there
is a possibility that the person will enter the imaging range of the video camera and
25 frame out (disappear) before being highlighted.
[0005] Some modes of the present invention were devised in view of the
foregoing problems, and one object of the present invention is to provide an
information processing system, an information processing method and a program
capable of suitably predicting an image of a video camera in which a moving body
30 appearing in a video camera will subsequently appear when tracking a person with a
plurality of video cameras.
[0006] The information processing system according to the present invention
comprises identification means for identifying a traveling direction of a moving body
appearing in an image of a first video camera among a plurality of video cameras, and
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prediction means for predicting, based on the traveling direction of the moving body in
the image of the first video camera, one or more second video cameras in which a
possibility of the moving body that is appearing in the image of the first video camera
subsequently appearing is higher than other video cameras among the plurality of
5 video cameras.
[0007] The information processing method according to the present invention is
an image processing method performed by an image processing system, the method
including: a step of identifying a traveling direction of a moving body appearing in an
image of a first video camera among a plurality of video cameras; and a step of
10 predicting, based on the traveling direction of the moving body in the image of the first
video camera, one or more second video cameras in which a possibility of the moving
body that is appearing in the image of the first video camera subsequently appearing
is higher than other video cameras among the plurality of video cameras.
[0008] The program according to the present invention causes a computer to
15 execute processing of identifying a traveling direction of a moving body appearing in a
image of a first video camera among a plurality of video cameras, and processing of
predicting, based on the traveling direction of the moving body in the image of the first
video camera, one or more second video cameras in which a possibility of the moving
body that is appearing in the image of the first video camera subsequently appearing
20 is higher than other video cameras among the plurality of video cameras.
[0009] Note that, in the present invention, terms such as "unit", "means", "device"
and "system" do not simply refer to a physical means, and include cases of realizing,
with software, the functions of such "unit", "means", "device" and "system".
Moreover, the functions of one "unit", "means", "device" or "system" may be realized
25 with two or more physical means or devices, and the functions of two or more "units",
"means", "devices" or "systems" may be realized with one physical means or device.
[0010] According to the present invention, it is possible to provide an information
processing system, an information processing method and a program capable of
suitably predicting an image of a video camera in which a moving body appearing in a
30 video camera will subsequently appear when tracking a person with a plurality of
video cameras.
DESCRIPTION OF DRAWINGS
[0011] Fig. 1 is a functional block diagram showing a schematic configuration of
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the monitoring system according to the first embodiment.
Fig. 2 is a diagram showing a specific example of the display screen.
Fig. 3 is a diagram explaining a specific example of the calculation method of
the appearance probability.
5 Fig. 4 is a functional block diagram showing a schematic configuration of the
information processing server illustrated in Fig. 1.
Fig. 5 is a flowchart showing the flow of processing of the information
processing server illustrated in Fig. 1.
Fig. 6 is a block diagram showing a configuration of the hardware capable of
10 mounting the information processing server illustrated in Fig. 1.
Fig. 7 is a functional block diagram showing a schematic configuration of the
monitoring device according to the second embodiment.
DETAILED DESCRIPTION
15 [0012] Embodiments of the present invention are now explained. The same or
similar symbol is given to the same or similar configuration in the description of the
drawings that will be explained and referenced below.
[0013] (1 First embodiment)
Fig. 1 to Fig. 6 are diagrams explaining the first embodiment. This
20 embodiment is now explained according to the following flow with reference to the
foregoing diagrams. Foremost, the outline of the system configuration is described
in "1.1", and the outline of the operation is explained in "1.2" while referring to specific
examples of a display screen and the like. Subsequently, the functional
configuration of the system is described in "1.3", the processing flow is described in
25 "1.4", and a specific example of the hardware configuration capable of realizing this
system is described in "1.5". Finally, effects and the like of this embodiment are
described in "1.6" onward.
[0014] (1.1 System configuration)
The system configuration of the monitoring system 1 as the information
30 processing system according to this embodiment is now explained with reference to
Fig. 1. Fig. 1 is a block diagram showing the system configuration of the monitoring
system 1.
[0015] The monitoring system 1 is generally configured from an information
processing server 100, a plurality of video cameras 200 (video cameras 200A to
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200N; hereinafter collectively referred to as the "video cameras 200"), a display
device 300, and an input device 400.
[0016] In the ensuing explanation, the monitoring system 1 is explained as a
system for monitoring (tracking) a person captured by the video cameras 200 as
5 imaging apparatuses, but the object to be monitored is not limited thereto. For
example, the object to be monitored may also be various moving bodies such as an
automobile, a bicycle, or a motorcycle.
[0017] The video cameras 200 capture images (videos) and determine whether
there is a person in the captured images, and send, together with the captured images,
10 the person detection result including information such as the position (including the
movement locus in the image) and feature quantity of the person in the image to the
information processing server 100. Moreover, the video cameras 200 can track the
person in the images (within the view angle) by comparing the captured images
between frames.
15 [0018] Note that processing of detecting the person, extracting the feature
quantity, and tracking the person in the camera does not need to be performed by the
video cameras 200, and may also be performed, for example, by the information
processing server 100 or another information processing apparatus not shown.
[0019] The information processing server 100 pervious various types of tracking
20 processing including the next camera prediction of predicting in which video camera
the person captured with the video camera 200 wiil subsequently appear by analyzing
the images captured with the video cameras 200.
[0020] Note that the images to be processed with the information processing
server 100 are not limited to the real-time images captured with the video cameras
25 200, it is also possible to track (analyze) the person based on the images that were
stored in a storage device (for example, HDD (Hard Disk Drive) or VCR (Video
Cassette Recorder)) after being captured with the video cameras 200.
[0021] In addition, it is also possible to track the person by playing the images
stored in the storage device backwards (reverse playback). Normally, when a
30 certain person engages in suspicious behavior, since it is necessary to check the path
and the actions that the person had taken before the foregoing suspicious behavior, it
is extremely useful to enable this kind of tracking based on reverse playback.
[0022] In the person monitoring based on the information processing server 100,
the information processing server 100 outputs various display screens such as a
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monitoring screen to the display device 300, and receives operation signals of various
operation inputs pertaining to the person monitoring from the input device 400. More
specifically, for example, by displaying a plurality of images input from the video
cameras 200 on the monitoring screen displayed on the display device 300 (specific
5 example is shown in Fig. 2 described later), the user as the monitor can comprehend
the current location of the person to be monitored.
[0023] The user as the monitor can view the display device 300 and, when the
person to be monitored appearing in the image (video) of a certain video camera 200
appears in an image of another video camera 200, operate the input device 400 and
10 associate the two persons as the same person. The information processing server
100 can thereby identify the moving path of the person. Note that the information
processing server 100 may also associate the persons, without manual operation,
based on information such as the feature quantity of the person appearing in the
images.
15 [0024] In addition, based on the traveling direction and speed of a person
appearing in a certain video camera 200, the information processing server 100
additionally has the next camera prediction function of predicting in which video
camera 200 that person wili subsequently appear. Since this prediction is performed
before the person frames out (disappears), even when the distance between the
20 video cameras 200 is short, the user as the monitor can reliably prepare to monitor the
subsequent video camera 200.
[0025] The display device 300 is a display for displaying images, for example, on
a liquid crystal or an organic EL (Electro Luminescence). The display device 300
displays the monitoring screen that is output from the information processing server
25 100.
[0026] The input device 400 is a device to be used by the user (monitor) for
inputting various types of information. For example, various pointing devices such
as a mouse, a touch pad or a touch panel, or a keyboard or the like correspond to the
input device 400. The various types of processing for registering the person to be
30 monitored, associating the registered person and the person that appeared in the
video camera 200 to the effect that they are the same person and the correction
thereof are performed based on the user's operations input using the input device
400.
[0027] Note that various configurations may be considered for the information
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processing server 100, and the display device 300 and the input device 400. For
example, the display device 300 and the input device 400 may be realized as one
client, or, otherwise, the functions of the information processing server 100, the
display device 300, and the input device 400 may be realized using three or more
5 information processing apparatuses. Moreover, when the display device 300 and
the input device 400 are realized as one client, a part of the functions of the
information processing server 100 of this embodiment may be performed by the client.
[0028] (1.2 Explanation of operation)
(1.2.1 Specific example of display screen)
10 Foremost, a specific example of the display screen displayed on the display
device 300 for person monitoring is explained with reference to Fig. 2. Fig. 2 is a
diagram showing a specific example of the display screen (hereinafter referred to as
the "monitoring screen 20") that is displayed by the display device 300 for person
monitoring.
15 [0029] In the example of Fig. 2, the monitoring screen 20 includes image areas
21A to 21D (hereinafter collectively referred to as the "image areas 21") which
respectively display the captured images input from a plurality of video cameras 200.
[0030] The image areas 21 display multi camera images input from a plurality of
video cameras 200 as described above. In the example of Fig. 2, the person P is
20 appearing in the image of the image area 21A. Let it be assumed that this person P
is advancing toward the traveling direction a. The information processing server 100
detects the traveling direction and speed of the person P, and predicts, based on the
detected traveling direction and speed, the image of the video camera 200 where that
person will subsequently appear, and the appearance position thereof. The
25 information processing server 100 selects and displays the image of the video camera
200 to be disposed in the image areas 21B to 21D consecutively in order of higher
possibility.
[0031] The images of the video cameras 200 displayed in the respective image
areas 21 switch continually (dynamically). For example, when the image in which
30 the probabiiity that the person will subsequently appear is high is changed pursuant to
the movement of the person to be monitored, the information processing server 100
sequentially switches the image of the image area 21 so that the images of the video
cameras 200 are arranged consecutively in order of higher possibility.
[0032] Appearance position suggestive images 23B to 23D (hereinafter
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collectively referred to as the "appearance position suggestive images 23") are
disposed on the respective image areas 21B to 21D. The appearance position
suggestive images 23 indicate the positions in the image where the person P to be
monitored is likely to appear. Here, the information processing server 100 may also
5 notify the level of possibility that the person P will appear by changing the color of or
flashing the appearance position suggestive images 23 according to the appearance
probability.
[0033] (1.2.2 Specific example of calculation method of appearance probability)
A specific example of the calculation method of the appearance probability of
10 the person appearing in an imaging area (that is, a captured image) of the respective
video cameras 200 is now explained with reference to Fig. 3. Fig. 3 is a diagram
explaining the calculation method of the appearance probability of the person P,
which is currently appearing in the image, appearing at the respective appearance
positions B1, B2, C1, D1, D2 as the appearance positions in the imaging range of the
15 video camera 200 where that person P may appear. In the example of this
embodiment, the appearance probability of the person P appearing at the respective
appearance position is calculated based on the following formula.
[0034] [Math 1 ]
Appearance probability = disappearance position arrival probability x appearance
20 position arrival probability
[0035] Here, the disappearance position arrival probability is the probability that
the person P appearing in the image V wiil respectively disappear at (frame out from)
the disappearance positions A1 to A3 that are set in advance in the image V.
Moreover, the appearance position arrival probability is the probability of the person P
25 appearing at the respective appearance positions after disappearing from the image V
at any one of the disappearance positions A1 to A3.
[0036] (1.2.2.1 Disappearance position arrival probability)
The disappearance position arrival probability can be calculated based on the
traveling direction and speed of the person P. In the example of Fig. 3, the
30 disappearance position arrival probability that the person P wiil respectively disappear
at (frame out from) the disappearance position A1 to disappearance position A3 is
0.01%, 65%, and 35%, respectively. Here, the reason why the disappearance
position arrival probability total exceeds 100% is because the significant figures have
been set to two digits.
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[0037] To explain this in further detail, the disappearance position A2 is located
on a substantially extended line of the traveling direction a. Thus, the disappearance
position arrival probability that the person P will head toward the disappearance
position A2 is highest.
5 [0038] While the disappearance position A3 is not located on the substantially
extended line of the traveling direction a, since it is located at the lower part of the
image V as with the disappearance position A2, it is considered that the possibility
that the person P will arrive at the disappearance position A3 is sufficiently high, and
thus the disappearance position arrival probability is high subsequent to the
10 disappearance position A2. The disappearance position A1 is located in a direction
that is opposite to the traveling direction a. Thus, the disappearance position arrival
probability of the person P appearing at the disappearance position A1 is of a
sufficiently low value.
[0039] Moreover, as described above, the speed of the person P can also be
15 considered upon calculating the disappearance position arrival probability. If the
position and speed of the person P are known, it is possible to predict the time
required for the person P to arrive at the respective disappearance positions A1 to A3.
For example, the longer the predicted time, it can be considered that the probability
that the person P will arrive at the respective disappearance positions A1 to A3 is iow.
20 [0040] Here, the relation of the direction and speed of the person P
(corresponding to the time required for the person P to arrive at the respective
disappearance positions A1 to A3) and the disappearance position arrival probability
may be set in advance based on an empirical rule, or statistically obtained based on
the movement of the numerous persons P appearing in the image V.
25 [0041] (1.2.2.2 Appearance position arrival probability)
The appearance position arrival probability can be calculated, for example, by
statistically seeking at which appearance position the person P that disappeared from
the respective disappearance positions A1 to A3 will appear. Otherwise, the
appearance position arrival probability may also be set in advance as a fixed value
30 based on based on an empirical rule,
[0042] In the example of Fig. 3, when the person P disappears from the
disappearance position A1 of the image V, it can be understood that the person P will
appear at the appearance position C1 with a probability of 100%. Similarly, when the
person P disappears from the disappearance position A2, it can be understood that
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the person P will appear at the appearance position D1 with a probability of 40%, and
appear at the appearance position D2 with a probability of 60%. Moreover, when the
person P disappears from the disappearance position A3, it can be understood that
the person P will appear at the appearance position B1 with a probability of 95%, and
5 appear at the appearance position B2 with a probabiiity of 5%.
[0043] Note that the time required for the person P to arrive at the respective
appearance positions from the respective disappearance positions A1 to A3 can also
be calculated based on the speed of the person P in the image V, and the distance
between each of the predetermined disappearance positions A1 to A3 and the
10 respective appearance positions.
[0044] (1.2.2.3 Appearance probability)
As described above, the appearance probability of the person P at the
respective appearance positions can be calculated based on the product of the
disappearance position arrival probability and the appearance position arrival
15 probability. In the example of Fig. 3, the appearance probabiiity at the appearance
position D2 is the highest at 39%, and subsequently in order of the appearance
position B1 (appearance probability 33%), the appearance position D1 (appearance
probabiiity 26%), the appearance position B2 (appearance probability 2%), and the
appearance position C1 (appearance probability 0.01%). Note that, because of
20 fractions, the total appearance probability in Fig. 3 is not 100%.
[0045] (1.3 Functional configuration of system)
Next, the functional configuration of the information processing server 100
according to this embodiment is explained with reference to Fig. 4. Fig. 4 is a
functional block diagram showing the functional configuration of the information
25 processing server 100 according to this embodiment.
[0046] As shown in Fig. 4, the information processing server 100 includes an
interior view angle person position acquisition unit 110, a disappearance position
arrival probability calculation unit 120, a database (DB) 130, an appearance position
arrival probability calculation unit 140, an appearance probability calculation/sorting
30 unit 150, and a display control unit 160.
[0047] The interior view angle person position acquisition unit 110 detects the
position of the person P appearing in the image of the video camera 200 based on the
person detection result that was input from the video camera 200. In addition, the
interior view angle person position acquisition unit 110 can also calculate the traveling
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direction and speed of the person P by analyzing the position of the person P in a time
series.
[0048] The disappearance position arrival probability calculation unit 120
calculates, for each disappearance position, the disappearance position arrival
5 probability indicating the likelihood that the person P will disappear at which
disappearance position in the image and the time required for the person P to arrive at
the respective disappearance positions based on the information acquired with the
interior view angle person position acquisition unit 110 and the inter-camera
information 131 stored in the DB 130. Here, the inter-camera information 131
10 includes information of the disappearance positions set in the image of the video
camera 200, and the various types of information required for the calculation of the
disappearance position arrival probability. Since the calculation method of the
disappearance position arrival probability was explained in foregoing "1.2.2.1", the
explanation thereof is omitted.
15 [0049] The appearance position arrival probability calculation unit 140 calculates
the probability that the person P will appear at the respective appearance positions
after disappearing from the respective disappearance positions. Since the
appearance position arrival probability was explained in foregoing "1.2.2.2", the
explanation thereof is omitted.
20 [0050] The appearance probability calculation/sorting unit 150 calculates the
probability that the person P will appear at the respective appearance positions based
on the disappearance position arrival probability calculated with the disappearance
position arrival probability calculation unit 120 and the appearance position arrival
probability calculated with the appearance position arrival probability calculation unit
25 140. Since the calculation method of the appearance probability was explained in
foregoing "1.2", the explanation thereof is omitted.
[0051] The display control unit 160 generates the monitoring screen 20 illustrated
in Fig. 2 based on the appearance probability for each of the appearance positions
calculated with the appearance probability calculation/sorting unit 150, and displays
30 the monitoring screen 20 on the display device 300. As described above, with the
monitoring screen 20 of Fig. 2, three images of the respective video cameras 200 are
selected and arranged consecutively in order of higher appearance probability, and
the appearance position in the respective image is shown with the appearance
position suggestive image 23.
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[0052] (1.4 Flow of processing)
The processing flow of the information processing server 100 is now explained
with reference to Fig. 5. Fig. 5 is a flowchart showing the processing flow of the
information processing server 100 according to this embodiment.
5 [0053] Note that the respective processing steps described later may be
executed by arbitrarily changing the order or in parallel to the extent that it is not
inconsistent with the processing contents. Moreover, another step may be added
between the respective processing steps. In addition, a step that is described as one
step as a matter of convenience may aiso be executed by being split into a plurality of
10 steps, and steps that are described by being split into a plurality of steps as a matter
of convenience may also be executed as one step.
[0054] Foremost, the interior view angle person position acquisition unit 110
acquires the position of the person P, which is appearing in the image of the video
camera 200, in the image based on the person detection result that was input from the
15 video camera 200 (S501). Moreover, the interior view angle person position
acquisition unit 110 additionally detects information such as the traveling direction and
speed of the person P.
[0055] Next, the disappearance position arrival probability calculation unit 120
calculates the disappearance position arrival probability of the respective
20 disappearance positions set in the image of the video camera 200 based on
information such as the traveling direction and speed of the person P detected with
the interior view angle person position acquisition unit 110 (S503). Here, the
disappearance position arrival probability calculation unit 120 additionally calculates
the time required for the person P to arrive at the respective disappearance positions.
25 [0056] When the person P disappears from the respective disappearance
positions of the image of the video camera 200 where the person P is currently
appearing, the appearance position arrival probability calculation unit 140 calculates
the appearance position arrival probability indicating at which appearance position the
person P will appear (S505).
30 [0057] The appearance probability calculation/sorting unit 150 respectively
calculates the appearance probabilities that the person P will appear at the
appearance positions of the respective video cameras 200 where the person P can
subsequently appear after the video camera 200 in which the person P is currently
appearing based on the disappearance position arrival probability calculated with the
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disappearance position arrival probability calculation unit 120 and the appearance
position arrival probability calculated with the appearance position arrival probability
calculation unit 140. In addition, the appearance probability calculation/sorting unit
150 rearranges (sorts) the respective appearance positions in order of higher
5 appearance probability (S509).
[0058] The display control unit 160 presents, to the user, the appearance
position in which the person P is likely to appear by using a display screen such as the
monitoring screen 20 illustrated in Fig. 2 in accordance with the appearance
probability calculated with the appearance probability calculation/sorting unit 150
10 (S511).
[0059] (1.5 Hardware configuration)
An example of the hardware configuration in the case of realizing the foregoing
information processing server 100 with a computer is now explained with reference to
Fig. 6. Note that, as described above, the functions of the information processing
15 server 100 may also be realized with a plurality of information processing
apparatuses.
[0060] As shown in Fig. 6, the information processing server 100 includes a
processor 601, a memory 603, a storage device 605, an input interface (l/F) 607, a
data l/F 609, a communication l/F 611, and a display device 613.
20 [0061] The processor 601 controls the various types of processing in the
information processing server 100 by executing the programs stored in the memory
603. For example, the processing pertaining to the interior view angle person
position acquisition unit 110, the disappearance position arrival probability calculation
unit 120, the appearance position arrival probability calculation unit 140, the
25 appearance probability calculation/sorting unit 150 and the display control unit 160
explained with reference to Fig. 4 may be realized as programs that are once stored in
the memory 603 and subsequently run on the processor 601.
[0062] The memory 603 is, for example, a storage medium such as a RAM
(Random Access Memory). The memory 603 temporarily stores program codes of
30 programs to be executed by the processor 601 and data that is required upon
executing the programs. For example, a stack area that is required upon executing
the programs is secured in the storage area of the memory 603.
[0063] The storage device 605 is, for example, a hard disk or a nonvolatile
storage medium such as a flash memory. The storage device 605 stores an
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operating system, and various programs for realizing the interior view angle person
position acquisition unit 110, the disappearance position arrival probability calculation
unit 120, the appearance position arrival probability calculation unit 140, the
appearance probability calculation/sorting unit 150, and the display control unit 160,
5 and various data including the inter-camera information 131 that is stored in the DB
130. The programs and data stored in the storage device 605 are referred to by the
processor 601 by being loaded into the memory 603 as needed.
[0064] The input l/F 607 is a device for receiving inputs from the user. The input
device 400 explained with reference to Fig. 1 can also be realized with the input l/F
10 607. As a specific example of the input l/F 607, considered may be a keyboard, a
mouse, a touch panel, or various sensors. The input l/F 607 may also be connected
to the information processing server 100 via an interface such as a USB (Universal
Serial Bus).
[0065] The data l/F 609 is a device for inputting data from the outside of the
15 information processing server 100. As a specific example of the data l/F 609, there
is a drive device for reading the data stored in-the various storage mediums. The
data l/F 609 may also be provided outside the information processing server 100. In
the foregoing case, the data l/F 609 is connected to the information processing server
100 via an interface such as a USB.
20 [0066] The communication l/F 611 is a device for communicating data via wired
or wireless communication with a device; for instance, the video camera 200 or the
like, that is outside the information processing server 100. The communication l/F
611 may also be provided outside the information processing server 100. In the
foregoing case, the communication l/F 611 is connected to the information processing
25 server 100 via an interface such as a USB.
[0067] The display device 613 is a device for displaying various types of
information. The display device 300 explained with reference to Fig. 1 may also be
realized with the display device 613. As a specific example of the display device 613,
considered may be, for example, a liquid crystal display or an organic EL
30 (Electro-Luminescence) display. The display device 613 may also be provided
outside the information processing server 100. In the foregoing case, the display
device 613 is connected to the information processing server 100 via a display cable
or the like.
[0068] (1.6 Effect of this embodiment)
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As described above, with the monitoring system 1 according to this embodiment,
the appearance position that the person to be monitored will subsequently appear
(image captured with the video camera 200 in which the person will subsequently
appear and the position that the person will appear in that image) is predicted while
5 the person is stiil appearing in an image of the video camera 200. Furthermore, the
user's monitoring load can be alleviated since the monitoring system 1 presents to the
user, based on the foregoing prediction, the image of the video camera 200 in which
the person is more likely to appear than the other video cameras 200 and the
appearance position thereof. In other words, the monitoring system 1 can suitably
10 predict an image of the video camera 200 in which a moving body appeanng in the
video camera 200 will subsequently appear.
[0069] (2 Second embodiment)
The second embodiment is now explained with reference to Fig. 7. Fig. 7 is a
block diagram showing the functional configuration of a monitoring device 700 as an
15 information processing system. As shown in Fig. 7, the monitoring device 700
includes an identification unit 710 and a prediction unit 720.
[0070] The identification unit 710 identifies the traveling direction of the moving
body appearing in a image of a certain video camera (hereinafter referred to as the
"first video camera" in this section) among a plurality of video cameras not shown.
20 Here, as specific examples of a moving body, in addition to a person, considered may
be an automobile, a bicycle, or a motorcycle.
[0071] The prediction unit 720 predicts, based on the traveling direction of the
moving body in the image of the first video camera, one or more video cameras
(hereinafter referred to as the "second video cameras") in which a possibility of the
25 moving body appearing in the image of the first video camera subsequently appearing
is higher than other video cameras among.
[0072] As a result of adopting the foregoing configuration, according to the
monitoring device 700 of this embodiment, it is possible to suitably predict a image of
a video camera in which a moving body appearing in a video camera will
30 subsequently appear when tracking a person with a plurality of video cameras.
[0073] (3 Supplementary information)
Note that the configuration of the foregoing embodiments may be combined or
partially replaced. Moreover, the configuration of the present invention is not limited
to the foregoing embodiments, and may be variously modified to the extent that the
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modification does not deviate from the gist of the present invention.
[0074] Note that a part or the hole of each of the foregoing embodiments may
also be described as per, but are not limited to, the following notes. Moreover, the
program of the present invention will suffice so as long as it is a program that causes a
5 computer to execute the respective operations explained in each of the foregoing
embodiments.
[0075] (Further exemplary embodiment 1)
An information processing system, comprising: identification means for
identifying a traveling direction of a moving body appearing in a image of a first video
10 camera among a plurality of video cameras; and prediction means for predicting,
based on the traveling direction of the moving body in the image of the first video
camera, one or more second video cameras in which a possibility of the moving body
that is appearing in the image of the first video camera subsequently appearing is
higher than other video cameras among the plurality of video cameras.
15 [0076] (Further exemplary embodiment 2)
The information processing system of further exemplary embodiment 1, wherein
the prediction means determines a first probability of the moving body heading toward
each disappearance position in the image, based on the traveling direction of the
moving body in the image of the first video camera, and predicts the second video
20 camera, based on a second probability in which the moving body heads to an imaging
position of another video camera from each disappearance position, and also based
on the first probability.
[0077] (Further exemplary embodiment 3)
The information processing system of further exemplary embodiment 1 or 2,
25 further comprising: display control means for displaying on a display device images of
the plurality of second video cameras, which are predicted by the prediction means,
consecutively starting from the image of the second video camera in which a
possibility of the moving body appearing next is highest.
[0078] (Further exemplary embodiment 4)
30 The information processing system of any one of further exemplary
embodiments 1 to 3, wherein the identification means identifies a traveling direction
and speed of the moving body, and the prediction means predicts the second video
camera based on the traveling direction and speed of the moving body.
[0079] (Further exemplary embodiment 5)
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The information processing system of any one of further exemplary
embodiments 1 to 4, wherein the prediction means predicts an appearance position of
the moving body in the image of the second video camera.
[0080] (Further exemplary embodiment 6)
5 An image processing method performed by an image processing system, the
method comprising a step of: identifying a traveling direction of a moving body
appearing in a image of a first video camera among a plurality of video cameras; and
a step of predicting, based on the traveling direction of the moving body in the image
of the first video camera, one or more second video cameras in which a possibility of
10 the moving body that is appearing in the image of the first video camera subsequently
appearing is higher than other video cameras among the plurality of video cameras.
[0081] (Further exemplary embodiment 7)
The information processing method of further exemplary embodiment 6,
wherein a first probability of the moving body heading toward each disappearance
15 position in the image is determined based on the traveling direction of the moving
body in the image of the first video camera, and the second video camera is predicted
based on a second probability in which the moving bodyl heads to an imaging
position of another video camera from each disappearance position, and also based
on the first probability.
20 [0082] (Further exemplary embodiment 8)
The information processing method of further exemplary embodiment 6 or 7,
further comprising a step of displaying on a display device images of the plurality of
second video cameras, which are predicted by the prediction means, consecutively
starting from the image of the second video camera in which a possibility of the
25 moving body appearing next is highest.
[0083] (Further exemplary embodiment 9)
The information processing method of any one of further exemplary
embodiment 6 to 8, wherein the second video camera is predicted based on a
traveling direction and speed of the moving body.
30 [0084] (Further exemplary embodiment 10)
The information processing method of any one of further exemplary
embodiment 6 to 9, wherein an appearance position of the moving body in the image
of the second video camera is predicted.
[0085] (Further exemplary embodiment 11)
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A program for causing a computer to execute: processing of identifying a
traveling direction of a moving body appearing in a image of a first video camera
among a plurality of video cameras; and processing of predicting, based on the
traveling direction of the moving body in the image of the first video camera, one or
5 more second video cameras in which a possibility of the moving body that is
appearing in the image of the first video camera subsequently appearing is higher
than other video cameras among the plurality of video cameras.
[0086] (Further exemplary embodiment 12)
The program of further exemplary embodiment 11, wherein a first probability of
10 the moving body heading toward each disappearance position in the image is
determined based on the traveling direction of the moving body in the image of the
first video camera, and the second video camera is predicted based on a second
probability in which the moving body heads to an imaging position of another video
camera from each disappearance position, and also based on the first probability.
15 [0087] (Further exemplary embodiment 13)
The program of further exemplary embodiment 11 or 12, wherein the program
causes a computer to further execute processing of displaying on a display device
images of the plurality of second video cameras, which are predicted by the prediction
means, consecutively starting from the image of the second video camera in which a
20 possibility of the moving body appearing next is highest.
[0088] (Further exemplary embodiment 14)
The program of any one of further exemplary embodiments 11 to 13, wherein
the second video camera is predicted based on a traveling direction and speed of the
moving body.
25 [0089] (Further exemplary embodiment 15)
The program of any one of further exemplary embodiments 11 to 14, wherein an
appearance position of the moving body in the image of the second video camera is
predicted.
[0090] This application relates to and claims priority from Japanese Patent
30 Application No. 2012-231086, filed on October 18, 2012, the entire disclosure of
which is incorporated herein by reference.
[0091] 1... monitoring system, 20... monitoring screen, 21... image area, 23...
appearance position suggestive image, 100... information processing server, 110...
interior view angle person position acquisition unit, 120... disappearance position
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arrival probability calculation unit, 130... database, 131... inter-camera information,
140... appearance position arrival probability calculation unit, 150... appearance
probability calculation/sorting unit, 160... display control unit, 200... video camera,
300... display device, 400... input device, 601... processor, 603... memory, 605...
5 storage device, 607... input interface, 609... data interface, 611... communication
interface, 613... display device, 700... monitoring device, 710... identification unit,
720... prediction unit

CLAIMS
I (We) claim:
1. An information processing system, comprising:
5 identification means for identifying a traveling direction of a moving body
appearing in an image of a first video camera among a plurality of video cameras; and
prediction means for predicting, based on the traveling direction of the moving
body in the image of the first video camera, one or more second video cameras in
which a possibility of the moving body that is appearing in the image of the first video
10 camera subsequently appearing is higher than other video cameras among the
plurality of video cameras.
2. The information processing system of claim 1,
wherein the prediction means determines a first probability of the moving body
15 heading toward each disappearance position in the image, based on the traveling
direction of the moving body in the image of the first video camera, and predicts the
second video camera, based on a second probability in which the moving body heads
to an imaging position of another video camera from each disappearance position,
and also based on the first probability.
20
3. The information processing system of claim 1 or claim 2, further comprising:
display control means for displaying on a display device images of the plurality
of second video cameras, which are predicted by the prediction means, consecutively
starting from the image of the second video camera in which a possibility of the
25 moving body appearing next is highest.
4. The information processing system of any one of claims 1 to 3, wherein
the identification means identifies a traveling direction and speed of the moving
body, and
30 the prediction means predicts the second video camera, based on the traveling
direction and speed of the moving body.
5. The information processing system of any one of claims 1 to 4,
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wherein the prediction means predicts an appearance position of the moving
body in the image of the second video camera.
6. An image processing method performed by an image processing system,
5 the method comprising:
a step of identifying a traveling direction of a moving body appearing in an
image of a first video camera among a plurality of video cameras; and
a step of predicting, based on the traveling direction of the moving body in the
image of the first video camera, one or more second video cameras in which a
10 possibility of the moving body that is appearing in the image of the first video camera
subsequently appearing is higher than other video cameras among the plurality of
video cameras.
7. A program for causing a computer to execute:
15 processing of identifying a traveling direction of a moving body appearing in an
image of a first video camera among a plurality of video cameras; and
processing of predicting, based on the traveling direction of the moving body in
the image of the first video camera, one or more second video cameras in which a
possibility of the moving body that is appearing in the image of the first video camera
20 subsequently appearing is higher than other video cameras among the plurality of
video cameras.