FIELD OF INVENTION:
The present invention relates to a method and system for controlling a digital device
remotely operated by human gesture or motion. More particularly, the present
invention is basically directed to develop a unique method and system which can
control any digital device such as laptops, desktops, tablets, phones, television, radio
and enables the device to perform all its regular activities like moving cursor,
rotating or moving objects like 3D models, zoom in or out the image, navigate into
2D and 3D maps, opening, closing, minimizing windows and many other applications
wherein this activities is initiated and controlled by the hand gesture of the user. The
present advancement involves minimum hardware for the said operation and a
digital device can be remotely operated by multiple users to simultaneously work on
a task, thus accelerating collaboration.
BACKGROUND OF THE INVENTION:
Digital devices in the past have been controlled by buttons, keys, and pointing
devices like mouse, laser pointer. Emulating natural human control by controlling
devices using human gesture is a new advancement. Digital devices have been
remotely controlled via audio inputs and remotely accessible pointing device inputs
provided by user. There have also been advancements in emulating touch gestures
by using touch screens as touch sensing devices in smartphones and tablets.
There have also been advancements in emulating hand gestures to remotely control
a digital device. Few outfits use neural signature sensors and gyroscopes on hand to
identify different neural signatures and thereby detect hand gesture. Other outfits
use Radio Frequency emitting devices on hand as input signals to be detected by a
sensor and thereby detecting motion of the hand.
Systems which use pointing devices or radio frequency emitting devices typically
required a bulky hardware along with them to detect correct hand gestures at high
speeds with a good amount of sensitivity. This blocks their use of remote control
hand gesture gadget as a portable and wearable one for use to control portable

digital devices like laptops, mobile phones, desktops, and even locale digital devices
like television because of wear-ability and usability issues.
Thus there has been a always need of a unique method and system which would
enable the remote controlling of different digital devices through a natural user
interface using gestures and motion control without involving any bulky dedicated
motion or gestures sensing devices. The method and the apparatus should be
capable of enabling any laptops, tablets, desktops etc. and effectively perform all
regular activities of the digital device. The device should be wearable, portable, and
ergonomically designed to ease user in emulating hand gestures to remotely control
digital devices.
OBJECT OF THE INVENTION:
It is thus the basic object of the present invention is to develop a unique method and
system which enables the controlling of different digital devices through a natural
user interface using gestures and motion control.
Another important object of the present invention is to provide a method and system
which can be easily associated with any laptops, tablets, desktops etc. and facilitates
the gestures based operation of the laptops, tablets, desktops.
Another important object of the present invention is to provide a gesture or motion
controlled handy and portable computing device which allows multiple users to
simultaneously work on a single computer on a single engineering design which
accelerates the development of engineering projects, hardware designs and robotics
designs.
Another object of the present invention is to provide a gesture or motion controlled
computation technique adapted to handle and edit 3D models, in architecture and
product designing.

A further object of the present invention is to provide a gesture or motion controlled
computation technique adapted to low coast 3-Dimensional scanning of physical
objects, generating their soft 3D designs and editing and modeling them.
Another object of the present invention is to provide a gesture or motion controlled
computation technique which can make computer gaming much more realistic with
physical involvement of users without involving any costly gaming devices.
A further object of the present invention is to provide a gesture or motion controlled
computation technique adapted to alleviate presentations and lectures in classrooms.
SUMMARY OF THE INVENTION:
A system for controlling operation of digital devices according to gesture of its user
comprising: at least one gesture indicating hardware; at least one imaging device for
capturing at least one first array of images of the at least one gesture indicating
hardware; and a processor for processing the captured stream of images for;
identifying at least one second array of images of the at least one gesture indicating
hardware from the at least one first array of images captured by the at least one
imaging device; determining at least one geometrical characteristic of bodies present
in the at least one second array of images and their variation to construct at least
one motion path of the at least one gesture indicating hardware; determining at least
one key coordinates point representing at least one motion path; and generating at
least one operating instruction to control at least one operation of at least one digital
device.
Noise cancellation while gesture detection is carried out by evaluating errors as a
function of relative distances, boundary distances, and characteristics of various
bodies identified beyond a threshold image size. Another approach of removing noise
in gesture detection is to fix the emitting device in a still environment and identifying
still bodies except emitter and thereby removing those still objects while capturing
emitting device in motion.

BRIEF DESCRIPTION OF THE ACCOMPANYING FIGURES:
Figure 1(a) shows an embodiment of the system of the present invention for
controlling the operation different digital devices based on the gesture of its user.
Figure 1(b) shows a preferred embodiment of gesture indicating hardware associated
with the present system of the present invention.
Figure 2 (a)-(c) schematically illustrates different geometrical characteristics involved
in the present system for detecting gesture of the user.
Figure 3(a)-(b) shows the pixel distribution in different bodies.
Figure 4(a)-(c) illustrates the mechanism for storing the sequence of the key
coordinates of motion of the gesture indicating hardware.
DETAILED DESCRIPTION OF THE INVENTION WITH REFERENCE TO THE
ACCOMPANYING FIGURES:
Reference is first invited from the accompanying figure 1(a) which shows an
embodiment of the system of the present system for controlling the operation
different digital devices based on the gesture of its user. The present system is
particularly adapted to be used in all types of different digital devices such as
laptops, tablets, desktops, smart phones etc. and enables the user to control and
interact with such digital device through a natural user interface using gestures and
motion control including the hand and finger movement.
As shown in the said figure, the present system for enabling any conventional digital
devices as gesture controlled devices comprises gesture indicating hardware 1 and
imaging device 2. The gesture indicating hardware 1 of the present system is a
device that prominently emits a selected range of electromagnetic radiation and the
imaging device 2 is an image sensor or a set of image sensors that capture the
image of the gesture indicating hardware 1 and detects or senses electromagnetic
radiation or signal emitted by the said gesture indicating hardware 1 along with
where the electromagnetic radiation or signal is coming from.

Reference is now invited from the accompanying figure 1(b) which shows a preferred
embodiment of the gesture indicating hardware 1. As shown in the said figure, the
gesture indicating hardware 1 is basically a tiny (less than an inch), wearable
(preferably on finger/thumb), slightly flexible (to fit comfortably in finger/thumb and
to adjust in different fingers of one or more persons), ring type device, with
specialized electronics embedded in it. The said gesture indicating hardware 1
comprises electromagnetic signal emitter 3 preferably IR emitter for generating and
thereby emitting the selected range of electromagnetic signal, a power source or
battery 4 for supplying electrical power to the emitter 3 and a push button switch 5
for selectively OFF/ON the emitter 3,
The selected range of electromagnetic signal emitted by the said emitter 3 may
correspond to a particular colour or a certain wavelength range of Infrared radiation
or any similar range.
In a preferred embodiment of the present system, which is used under sun light, the
emitter 3 of the gesture indicating hardware 1 is specially developed to generate
infrared radiation around 350-1450 nm and 1700 nm to avoid the problem of sun's
interference with the emitter radiation as the sun's radiation is minimum at the
above mentioned range. The imaging device 2 also involves CMOS sensor specially
adapted for detecting or sensing the infrared radiation around 350-1450 nm and
1700 nm.
The imaging device 2 of the present system may be in a separated module adapted
to be operatively connected with the digital device 6 by using USB or other
connection 7 or can be built in the digital devices. The working of the imaging device
2 is further enhanced by using one or more filters to avoid any other electromagnetic
radiation with wavelength range except the range/ranges emitted by the gesture
indicating hardware 1 mentioned above. This will reduce the noise and significantly
reduce the processing required. The Images or the sensory data captured per second
i.e. Frames Per Second by the image sensors is kept almost constant by fixing the
time of exposure of the imaging device 2 for capturing one image. By keeping the
time of exposure low, the light entered per image can be minimized, hence the
removal of everything else, except the strong electromagnetic radiation or signal

having selective wavelength range from the emitters 3 would be possible by using
electromagnetic signal filter having pass band matched with the selected wavelength
range.
Now, for smoothing the sensing or imaging of motion of the gesture indicating
hardware 1, the number of images captured per second or frame per second (fps) is
increased. In a preferred embodiment of the system of the present invention, the
imaging device 2 involves multiple image sensors with lower fps in a selective
fashion to constitute a single image sensor with higher fps. For example, in an
embodiment, wherein the imaging device 2 involves two image sensors of m fps, the
assembly of the two sensors are converted into a single sensor of 2m fps. This is
done by starting the first sensor and then starting the second sensor after l/2m
seconds of the first sensor. Hence the two sensors combined, starts providing images
at an interval of l/2m seconds reaching effectively 2m fps. In the said embodiment,
these two sensors are kept nearby and standard stereo vision technique is used to
find the position of the emitter 3 in 3-Dimensional space.
The image sensors of the imaging device 2 is also adapted to simultaneously detect
or sense electromagnetic radiations or signals emitted by the multiple gesture
indicating hardware along with their location for allowing multiple people to use the
same device.
The system of the present invention also comprises a processor in the imaging
device adapted for detecting and thereby separating the gesture indicating hardware
image from neighboring environment and determining data relating to consecutive
positions, orientations and distance of the said gesture indicating hardware to
identify the gestures and accordingly provide instruction to the digital device to
perform desired activities.
In preferred of the present system wherein the imaging device 2 operatively
connected to any conventional Television set is adapted to continuously detect the
signal emitted by the remote of the television set and thereby detect motion path of
the remote while emitting signal to identify the gestures and accordingly control the
operation of the television set. Hence by using the present system, the remote of
any usual television set can be used as the gesture indicating hardware to enable the

television set gesture operated. In such application the remote of the television
circuit is modified by incorporating additional operating switches to enable the
remote for continuously emit signal during the gesture.
In the present system, the identification and the separation of the images of the
different emitters from the imaging device captured complete images is performed
by the said processor by analysing different attributes of the captured images.
The different attributes of the captured images involved for identifying and
separating the images of different emitters includes colour content and their
distribution, geometrical characteristics, motion characteristics and removal of pre-
stored environmental disturbances, previous positions and motion of the emitters in
the captured images and the distribution of pixels in the captured image at different
distances from an assigned centre.
In the present invention, for separating the images of the different emitters on the
basis of colour content a particular colour and a threshold value around it is chosen
and only the pixels in the captured image having colour value lying within this range
are considered for further processing. In a preferred embodiment of the present
system, wherein the emitter prominently emits a selected range of Electromagnetic
radiations, a certain distribution of colour and colour intensity is found in the
captured Image. In such distribution the maximum intensity is encountered in the
centre and the coloured part is observed at a certain distance from the centre. Hence
if a colour distribution is found within the captured Image, it is considered as a
signature for Identification of the emitter in the captured image. In case the emitter
emits in a range of electromagnetic radiation or signal that can not be resolved by
normal Image sensor into any colours, the Image of the emitter appears like a
monochromatic image having highest intensity (brightness) at a point in the image
and it decreases as a function of the distance from the point. Hence if there is an
intensity distribution within the Image, it is considered as one of the signature for
Identification of the emitter in the captured image.
In the present system, the processor comprises a pixel intensity computing module
for determining the intensity of the pixels in the image sensors captured image and
finding the pixels in the image having highest intensity with the pixels with

decreasing intensity as a function of the distance from the said highest intensity
pixels to locate the emitters in the image.
In the present invention, for separating the images of the different emitters from the
captured image stream on the basis of geometrical characteristics, different bodies
present in the captured image formed by a set of connected pixels is first identified
and a unique tag number is allotted to each of the identified body or the set of
connected pixels and then all the pixels inside the tagged body is tagged with that
unique tag number. After the tagging operation all bodies are analysed for identifying
the image of the emitter. The method for identifying the image of the emitters on the
basis of geometrical characteristics firstly involves assigning a point in body present
in the captured image that can be taken as a centre of the body. This can be done by
assigning a point as the centre of the body where the first or higher moment
calculated using the pixels of the set of connected pixels is zero or the point where
the total intensity or intensity of selected colours is highest (In case of many such
points exists, centroid of them is taken) or the point that is calculated using the
weighted average of the pixels in the image of the body where the weights are some
function of intensities of corresponding pixels. After assigning the centre diameter of
the body is determined. Here, diameter refers to the longest chord connecting two
oppositely lying pixels on the boundary of the body parallel to a mentioned direction.
If there is no direction mentioned, then the diameter refers to the longest chord. The
radius in that direction will be half of the diameter in that direction. The directional
radius is approximated by finding the distance between the assigned centre and the
boundary pixel at the given angle (direction) for determining the directional
(angular) radius. Diameter along that direction can be taken as twice the directional
radius. Diameter parallel to that direction can be taken as the sum of the two radii,
along and opposite to the direction.
The accompanying figure 2(a) shows the boundary pixel B and assigned centre A of
the body. The distance AB will be the radius at that angle/direction.
The distance between two bodies present in the captured image streams is
approximated as, the distance between their assigned centres and the boundary
distance between two bodies is approximated as:

Case 1: If the two bodies don't have any pixels in common, then two assigned
centres are joined with a straight line and the minimum distance between the
boundary pixels of the bodies through which this line passes through is assigned as
the boundary distance. The accompanying figure 2(b) shows the boundary distance
between two bodies as distance AB.
Case 2: If the two bodies have some pixels in common which is mostly occurs when
the image of same body is captured in an interval of few milliseconds. A negative
value is assigned as the boundary distance having magnitude equal to the ratio of
number of overlapping pixels to function of total number of pixels in both images.
In the present system, the said processor in the imaging device also comprises
computation unit adapted to calculate the first or higher moment by using the pixels
of the set of connected pixels forming a bodies in the image streams and find where
it is zero for assigning that as the centre of the body. The said computation unit also
calculates the radii of the bodies and the distance between two bodies present in the
captured image streams.
Now, the emitting device identified in an image frame is tracked in the subsequent
image frames by involving the ratio of various directional radii of the bodies in the
subsequent frames to that of the previous selected body identified as the emitter to
find the deviation in the directional ratio. The body corresponding to the emitter in
the subsequent image frames will have the highest probability of having the lowest
deviation from the body that is identified as a particular emitting device in previous
selected body. In the present system the computing unit of the processor calculates
the ratio of various directional radii of the bodies in the subsequent frames to that of
the previous selected body identified as the emitter. The processor of the present
system also includes a comparator module to compare the ratio values and find the
directional ratio for the body in the subsequent frames showing least deviation to
find the emitters in the subsequent image frames.
The Distance of a particular body from the previous selected body identified as a
particular emitting device is a very important factor. Lower the distance, higher the
probability of the body being the emitting device. The Boundary distance of a
particular body from the said previous selected body is another very important

factor. Lower the boundary distance, higher the probability of the body being the
emitting device.
Every image is captured by exposing the image sensor for a small time interval. Due
to this time interval, images of moving objects are distorted. This is because the light
reflected/emitted from the moving object comes from different positions that it takes
due to its motion during time of exposure of that frame. Due to the component of
velocity, parallel to the plane of sensor, the image captured is elongated in the
direction of velocity with respect to the imaging sensor. This elongation is
proportional to that component of speed with respect to sensor and distance from
the sensor. Hence the length of such object image is increased in the direction
parallel of object velocity while the length of such object image remains almost
unchanged in the directions perpendicular to the object velocity. In the present
system, the processor interprets the movement of the gesture indicating hardware
by continuous calculating the variation in the geometrical characteristics including
diameter of the emitter in the image streams. It is also important to note that the
deviation in radius of the identified emitter body perpendicular to the direction of the
velocity remains almost unchanged and represents the approximate distance of the
emitting device from the image sensors. Hence, the adaptability of determining
deviation in radius of the identified emitter body enables the present system to
determine distance of the gesture indicating hardware from the imaging device.
In the present invention, for facilitating the separation of the images of the different
emitters on the basis of motion characteristic and removal of pre-stored
environmental disturbances, the imaging device of the present system is first
initialized before initiating the emitters so that the image sensors of the imaging
device capture image of the bodies present around the gesture indicating devices. All
the pixels of these bodies in the image are stored and listed as disturbance pixels.
After the initiation of the emitters, during normal functioning, whenever any pixel of
any body is found as one of these disturbance pixels, the body is discarded as a
disturbance.

A further enhancement in the said separation process is done by checking the
geometrical and colour characteristics before discarding the body by comparing it
with the characteristics of disturbance body.
In the present invention, the motion characteristics analysis indicates the amount of
motion done by the bodies in the captured image including the body identified as the
emitter in a particular frame. Describing below the method of calculation of motion
characteristics:
Consider two consecutive frames, first one as 'A' and the frame immediately after
that as 'B'. Consider a particular body 'a' in frame 'B'. All the pixels of body 'a' are
considered and the same pixels in the last frame are checked. Considering a total of
n pixels among them are found to be a part of any body in the frame 'A', then the
motion characteristics will be proportional to:
(Total number of pixels in body 'a'-n) / (Total number of pixels in body 'a')
Higher the motion characteristics of the body higher will be motion of the body.
Motion characteristics = 0, implies that there is high chance, that body is static.
Motion characteristics = 1, implies that there is a high chance that body have
performed a good amount of motion. Motion characteristics anything between 0 and
1 implies that there is some motion, the magnitude of which is proportional to the
value of motion. The computation unit of the processor of the present system
computes the above equation to find the motion characteristics.
In the present invention, for separating the images of the different emitters on the
basis of previous positions and motion the position information of last frames is
involved to predict the position of bodies in the current frame. This is done by simple
mathematical extrapolation techniques. The deviation of the position of body in
current frame, from the predicted position facilitates in finding the body
corresponding to the emitting device. Assuming that we correctly identified the
hardware device in last frame, and predicted its position in the current frame, then
the body with least deviation from the prediction, will have the highest chance of
being the emitting device.

In the present invention, the distribution of, number of pixels at different distances
from the assigned centre is analysed to identify different bodies in the image
uniquely. For example a perfect circle, all the points will be at same distance from
the centre. So the distribution will be something like the accompanying figure 3(a)
while for an elliptical shape the distribution will be something the accompanying
figure 3(b).
Once all the bodies and the emitting devices in current frame and in previous frame
are identified the mapping between the bodies in two consecutive frames i.e. which
body in current frame was which body, in last frame is executed. The mapping
further facilitates to identify if a body in the captured image is the emitting device or
not, as well as it will also help to judge that which body corresponds to which
emitting device in case of multiple emitting devices.
After separation of the emitter images from rest of the image, and mapping them,
the motion of the gesture indicating hardware is interpreted. If the user/users are
wearing the device in different fingers, then by judging motion of the gesture
indicating hardware the motion of fingers is interpreted.
For recognising the gesture of the user, the processor of the present system
accumulates stream of the separated images of the gesture indicating hardware from
the captured image stream and constitutes the motion path of the gesture indicating
hardware. After constituting motion path of the gesture indicating hardware the key
coordinate points of the motion path is determined by the coordinate computation
module of the processor. The operating instruction for controlling operation of the
digital devices is generated in accordance with the sequence of the key coordinate
points. The processor also comprises memory device for storing user specific gesture
assigned to perform any particular operation of the digital device as a sequence of
the key coordinate points of motion of the gesture indicating hardware. The stored
sequence of the coordinates is compared with the determined coordinates of the
motion path of the gesture indicating hardware and performs the assigned operation
in the digital device on matching of the sequence of the stored and the determined
coordinates.

The accompanying figures 4(a)-(c) illustrates the mechanism for storing the
sequence of the key coordinates of motion of the gesture indicating hardware. As
shown in the figure 4(a), the discrete points represent the coordinates that
represents the motion path when a user moves the gesture indicating hardware to
make "A". All the coordinates are smoothed by averaging each coordinate by some
neighbour coordinates to remove any noise or irregularity. Now from this Key
coordinate points (KP) are determined. The KPs are the points such that the angle
between the tangents of two KPs becomes equal to or greater than a particular
threshold value. The accompanying figure 4(b) shows two dots where the angle
between them becomes the threshold value 'A'. The two points a and b thus
becomes KPs. Threshold is chosen by the user. The accompanying figure 4(c) shows
all the KPs of the gesture "A" with sequence number written. These KPs are stored in
the memory device and whenever user(s) makes any gesture like A the present
system rescale the gesture to the stored gesture and find out all the KPs and match
it with KPs of stored gesture. If they matched with a small error, then the gesture is
recognised and the corresponding process is performed.
It is thus possible by way of the present advancement to enable digital device
gesture or motion operated digital device operation and use which can be associated
with any digital device such as laptops, desktops, tablets, phones and enables the
device to perform all its regular activities. Further the detection of the gesture based
on the deviation on the geometrical characteristics enables the present system for
3D tracking only from one normal image is itself new and it was apparently
impossible before the invention. The present system advantageously involves
previous frames and some standard inputs to calculate apparent distance from
imaging device results 3D interpretation.
Another embodiment of the present invention is a process to identify gesture and
motion path as described below:
1. An array of sequential images is captured via image capturing device also
capturing the emitting device. The color coordinate is transformed for easy
identification and seperation of emitter.
2. A point in the color coordinates corresponding to the emitter is selected and
all the pixels in the image lying in a narrow range of that point are taken and
a separate image is formed from these points.

3. All the bodies beyond a particular threshold size are identified in the image.
4. The position of the emitters in the previous frame is taken to sort all the
bodies in current frame in an increasing order of distance from it.
5. The images of emitting device are separated from complete image and
different devices are identified distinctly.
6. Coordinates of different devices in the image are identified. Either the
rescaled coordinates or the rate of change of these coordinates are used to
control the pointer. Various gesture are identified from the motion of single
emitter or the relative position of different emitters and used to initiate,
control or close different applications. Users get the flexibility to store their
own gestures and assign a different task for each gesture.
Noise reduction in the process of gesture recognition mentioned above comprises:
1. The bodies of size (number of pixels) smaller than a particular value are
rejected as noises.
2. For fast processing, we calculate the directional radius at 8 angles, 0*45
,1*45, 2*45, 3*45, 4*45, 5*45, 6*45, 7*45 degrees, (* means
multiplication) and take the ratio of each directional redius with the
corresponding directional radius of the an emitter in previous frame. These
ratios are summed up and 8 is substracted from this value. This gives the
error involved in shape.
R[0][previous]/R[0][current] + R[45][previous]/R[45][current]
R[7*45][previous]/R[7*45][current] - 8
All the angles are measured with respect to
(i) either the direction between assigned centres of previously selected body
and the body considered.
(ii) or the direction of the longest diameter of the body considered.
3. The boundary distance and the distance gives another error.

4. The ratio of radius perpendicular to the direction of the velocity of previously
selected body to body considered is taken and 1 is subtracted from it thus
allowing us to quantify another error:
Rp[previous]/Rp[current] - 1
5. Motion characteristics is calculated as described in the draft and 1-motion
characteristic gives another error.
6. The deviation of the body from the predicted position as described in the draft
under "On the basis of previous positions and motion" gives another error.
7. Some other errors are calculated
8. Finally, the allowable range of each error is determined experimentally. The
experiment can be done easily by instructing the user to move the emitter on
a prescribed path at different speeds. Maximum errors in the experiment will
give the allowable range of errors. All the bodies with one or more error
considerably more than the allowable range, will be rejected.
Another embodiment of the present invention is a system and process to track
position and orientation of a three dimensional body. Three emitters/markers are
attached in the single plane forming an equilateral triangle. Another emitter is
attached in the middle of three emitters in a plane other than the first plane.
Since one image sensor in the xy plane gives the x and y coordinated only, the
distance between every pair of emitters is same (equilateral triangle). So we can
form an equation by equating the distances by assuming there z coordinates as Zl ,
Z2, and Z3.
This will give us the equation,
(X1-X2)^2 + (Y1-Y2)^2 + (Z1-Z2)^2 = (X1-X3)^2 +(Y1-Y3)^2 +(Z1-Z3)^2 =
(X2-X3)^2 +(Y2-Y3)^2 +(Z2-Z3)^2

Taking X1, Y1 and Z1 as reference, that is taking them 0, 0, 0 and
solving this equation, one can find the coordinates Z2 and Z3 in terms of other x and
y coordinates. Z2 and Z3 thus found will be in reference to Z1.
This can be used to find the physical side length of the triangle, which is proportional
to the distance of the triangle from the sensor. One can also find the orientation of
the triangle in three dimensions using this information.
The conflict of signs of Z1 and Z2 can be resolved using the position of the fourth
light with respect to the centroid of the three coordinates in first plane.

We claim:
1. A system for controlling operation of digital devices according to gesture of
its user comprising:
at least one gesture indicating hardware;
at least one imaging device for capturing at least one first array of images of
the at least one gesture indicating hardware; and
a processor for processing the captured stream of images for;
identifying at least one second array of images of the at least one
gesture indicating hardware from the at least one first array of images
captured by the at least one imaging device;
determining at least one geometrical characteristic of bodies present in
the at least one second array of images and their variation to construct
at least one motion path of the at least one gesture indicating
hardware;
determining at least one key coordinates point representing at least
one motion path; and
generating at least one operating instruction to control at least one
operation of at least one digital device.
2. The system as claimed in claim 1, wherein the at least one gesture indicating
hardware comprises at least one electromagnetic signal emitter for
generating and emitting electromagnetic signal detectable by the at least
one imaging device.
3. The system as claimed in claim 2, wherein the at least imaging device
comprises at least one image sensor adapted to capture at least one image
of the at least one gesture indicating hardware and detect the

electromagnetic signal emitted by the at least one electromagnetic signal
emitter of the at least one gesture indicating hardware.
4. The system as claimed in anyone of the claims 1 to 3, wherein the at least
one imaging device is provided In a separated module adapted to be
disposed in operative communication with the at least one digital device.
5. The system as claimed in anyone of the claims 1 to 3, wherein the at least
one imaging device is built in the at least one digital devices.
6. The system as claimed in anyone of the claims 1 to 5, wherein the at least
one imaging device further comprises at least one electromagnetic signal
filters adapted to block any other electromagnetic radiation or signal except
the electromagnetic signal emitted from the at least one electromagnetic
emitter.
7. The system as claimed in anyone of the claims 1 to 6, wherein the at least
one imaging device further comprises at least two image sensors adapted to
constitute a single image sensor with high imaging capturing rate for
smoothing imaging of motion of the at least one gesture indicating hardware.
8. The system as claimed in the claim 7, wherein the at least one imaging
device comprises two image sensors with imaging capturing rate of value m
are adapted to operate as individual imaging devices, each comprising single
image sensors with imaging capturing rate of 2m by initiating one of the
image sensors l/2m seconds before the second image sensor.
9. The system as claimed in the claim 8, wherein the two image sensors are
placed relatively at a position to obtain standard stereo vision is obtained.
10. The system as claimed in anyone of the claims 1 to 9, wherein the processor
for identifying and separating the images of the gesture indicating hardware
comprises:
at least one pixel intensity computing module adapted to determine
intensity distribution of pixels in an array of images captured by at

least one image sensor to locate the at least one electromagnetic
signal emitter in the image;
at least one computation unit adapted to calculate different
geometrical characteristics of different bodies represented by set of
connected pixels in the array of images and ratio of the geometrical
characteristics of the different bodies in an image frame to that of the
body identified as the at least one electromagnetic signal emitter in an
previous frame; and
at least one comparator module adapted to compare the ratio values
and identify at least one electromagnetic signal emitter as a body for
which the ratio shows least deviation in the array of images.
11. The system as claimed in anyone of the claims 1 to 9, wherein the at least
one pixel intensity computing module is adapted to locate the at least one
electromagnetic signal emitter in the image by determining the pixels in the
image having highest intensity with surrounding pixels having decreasing
intensity as a function of the distance from the said highest intensity pixels.
12. The system as claimed in anyone of the claims 1 to 11, wherein the at least
one computation unit is adapted to calculate point in the bodies in the image
where first or higher moment of a set of connected pixels representing the
bodies in the captured image is zero or a point where an intensity or
intensity of selected colours is highest for assigning a centre in the body.
13. The system as claimed in the claim 11, wherein the at least one computation
unit is adapted to calculate the geometrical characteristics including radii of
the bodies, distance between two bodies present in the image streams with
reference to the assigned centre.
14. The system as claimed in anyone of the claims 1 to 13, wherein the at least
one computation unit is adapted to determine motion state of the bodies in
the array of captured images by calculating a ratio of total number of pixels
in body 'a' minus n to the total number of pixels in body 'a';

wherein, 'a' represents a particular body in later frame of any two consecutive
image frames selected from the array of captured images and n is total
number of pixels that are found to be a part of any body in an earlier frame of
the two consecutive image frames.
15.The system as claimed in anyone of the claims 1 to 14, wherein the at least
one processor is adapted to detect the movement of the at least one gesture
indicating hardware including its distance from the at least one imaging
device by continuously calculating variation in geometrical characteristics of
the at least one electromagnetic signal emitter in the array of captured
images.
16. The system as claimed in anyone of the claims 1 to 13, wherein the
processor further comprises coordinate computation module adapted to
identify the motion path representing key coordinates points by finding pair
of coordinate points in the motion path at which angle between tangents is
equal to or greater than a user defined threshold value.
17. The system as claimed in anyone of the claims 1 to 16, wherein the processor
comprises memory devices adapted to store user specific gesture assigned to
perform any particular operation of the digital device as a sequence of the key
coordinate points;
wherein the stored sequence of the key coordinate points is compared with
the determined key coordinates of the motion path of the gesture indicating
hardware and performs the assigned operation in the digital device on
matching of the sequence of the stored and the determined key coordinates.
18. A method for operating digital devices according to gesture of its user by
involving the system as claimed in anyone of the claims 1 to 17 comprising:

continuously capturing images of the at least one gesture indicating
hardware;
locating a specific intensity distribution of the pixels of captured images to
identify an image of the at least one electromagnetic signal emitter associated
with the at least one gesture indicating hardware in the array of captured
images;
determining the geometric characteristics of the set of connected pixels
representing different bodies in the array of captured images;
identifying the emitter in the subsequent image streams by comparing the
geometric characteristics of the bodies with the same of the body identified as
the at least one electromagnetic signal emitter in the previous image frame;
determining variation in the geometric characteristics of the body identified as
the at least one electromagnetic signal emitter in the array of captured
images to detect the movement of the gesture indicating hardware including
its distance from the imaging device;
constituting the motion path of the at least one gesture indicating hardware
and determining sequence of the key coordinate points in the motion path;
and
generating operating instructions to control the at least one digital devices in
accordance with the sequence of the at least one key coordinate points in the
motion path.