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Gesture recognition
Gestures are an important aspect of human
interaction, both interpersonally and in the
context of man-machine interfaces.
A gesture is a form of non-verbal communication
in which visible bodily actions communicate
particular messages, either in place of speech or
together and in parallel with words.
Gestures include movement of the hands, face, or
other parts of the body.
Military air marshals use
hand and body gestures to
direct flight operations
aboard aircraft carriers.
Gesticulation:-
Spontaneous movements of the hands and arms that
accompany speech.
Language-like gestures:-
Gesticulation that is integrated into a spoken
utterance, replacing a particular spoken word or phrase.
Pantomimes:-
Gestures that depict objects or actions, with or without
accompanying speech.
Emblems:-
Familiar gestures such as V for victory, thumbs up, and
assorted rude gestures.
Sign languages.:-
Linguistic systems, such as American Sign Language, which
are well defined.

What is
Gesture Recognition ?
Interface with computers using gestures of
the human body, typically hand movements.
Gesture recognition is an important skill for
robots that work closely with humans.
Gesture recognition is especially valuable in
applications involving interaction
human/robot for several reasons.
A child being
sensed by a
simple
gesture
recognition
algorithm
detecting
hand location
and
movement.
A basic working of the gesture
recognition system
Hand gesture recognition
is one obvious way to
create a useful, highly
adaptive interface
between machines and
their users.
Hand gesture recognition
technology would allow for
the operation of complex
machines using only a
series of finger and hand
movements, eliminating
the need for physical
contact between operator
and machine.
Facial gesture recognition
is another way of creating
an effective non-contact
interface between users
and their machines.
The goal of facial gesture
recognition is for machines
to effectively understand
emotions and other
communication cues
within humans, regardless
of the countless physical
differences between
individuals.
Sign language
recognition is one of
the most promising
sub-fields in gesture
recognition research.
Effective sign
language recognition
would grant the deaf
and hard-of-hearing
expanded tools for
communicating with
both other people and
machines.
Gesture Sensing Technologies:-
 Device Gesture Technologies
 Vision-based Technologies
 Electrical Field Sensing
Touch based gestures
Non-Contact:
Contact type:
 Device-based techniques
use a glove, stylus, or
other position
tracker, whose
movements send signals
that the system uses to
identify the gesture.
 The glove is equipped
with a variety of sensors
to provide information
about hand
position, orientation, and
flex of fingers.
There are two approaches
to vision based gesture
recognition:
Model based techniques:
They try to create a three
dimensional model of the
users hand and use this for
recognition.
Image based methods:
Image-based techniques
detect a gesture by
capturing pictures of a
user’s motions during the
course of a gesture.
Proximity of a human
body or body part can be
measured by sensing
electric fields .
These measurements can
be used to measure the
distance of a human
hand or other body part
from an object; this
facilitates a vast range of
applications for a wide
range of industries.
These can provide input to the computer
about the position and rotation of the hands
using magnetic or inertial tracking devices.
The first commercially available hand-
tracking glove-type device was the Data
Glove , a glove-type device which could
detect hand position, movement and finger
bending.
This uses fiber optic cables running down
the back of the hand. Light pulses are
created and when the fingers are bent, light
leaks through small cracks and the loss is
registered, giving an approximation of the
hand pose.
Wired gloves:-
A Stereo camera is a camera that has
two lenses about the same distance
apart as your eyes and takes two
pictures at the same time. This
simulates the way we actually see
and therefore creates the 3D effect
when viewed.
Using two cameras whose relations
to one another are known, a 3D
representation can be approximated
by the output of the cameras.
Stereo cameras:-
Gesture recognition
Using specialized cameras such
as structured light or time-of-flight
cameras, one can generate a depth
map of what is being seen through
the camera at a short range, and use
this data to approximate a 3d
representation of what is being
seen.
These can be effective for detection
of hand gestures due to their short
range capabilities.
Depth-aware cameras.
Gesture recognition
Technology Behind It:-
Thermal cameras:
An infrared camera is a device that
detects infrared
radiation(temperature) from the
target object and converts it into an
electronic signal to generate a
thermal picture on a monitor or to
make temperature calculations on it.
The temperature which is captured
by an infrared camera can be
measured or quantified exactly, so
that not only the thermal behavior
can be observed but also the relative
magnitude of temperature related
problems can be recognized and
noted.
Gesture recognition
These controllers act as an extension of the body so that when
gestures are performed, some of their motion can be
conveniently captured by software.
Mouse gestures are one such example, where the motion of
the mouse is correlated to a symbol being drawn by a
person's hand, as is the Wii Remote, which can study changes
in acceleration over time to represent gestures.
Controller –based gestures:-
A normal camera can be used for gesture recognition where the
resources/environment would not be convenient for other forms of image-
based recognition.
Earlier it was thought that single camera may not be as effective as stereo
or depth aware cameras, but a start-up based out of Palo Alto
named Flutter is challenging this theory. It has released an app that could
be downloaded to by any windows/mac computer with built-in webcam.
Single camera:-
3D model-based algorithms
Skeletal-based algorithms
Appearance-based models
3D model-based algorithms:-
A real hand (left) is interpreted as a collection of
vertices and lines in the 3D mesh version
(right), and the software uses their relative
position and interaction in order to infer the
gesture.Skeletal based algorithms:-
The skeletal version (right) is effectively modelling
the hand (left). This has fewer parameters than the
volumetric version and it's easier to
compute, making it suitable for real-time gesture
analysis systems
Appearance based models:-
These binary silhouette(left) or contour(right)
images represent typical input for appearance-
based algorithms. They are compared with
different hand templates and if they match, the
correspondent gesture is inferred.
Socially assistive robotics:-
Sign language
recognition:-
By using proper sensors worn on the body of a
patient and by reading the values from those
sensors, robots can assist in patient
rehabilitation. The best example can be stroke
rehabilitation.
Just as speech recognition can
transcribe speech to text,
certain types of gesture
recognition software can
transcribe the symbols
represented through sign
language into text.
Virtual controllers:-
Remote control:-
Through the use of gesture
recognition, remote control with the
wave of a hand of various devices is
possible.
For systems where the act of finding or
acquiring a physical controller could require too
much time, gestures can be used as an
alternative control mechanism. Controlling
secondary devices in a car, or controlling a
television set are examples of such usage.
Control through facial gestures:-
Immersive game
technology:-
Gestures can be used to control
interactions within video games to
try and make the game player's
experience more interactive or
immersive.
Controlling a computer through facial gestures
is a useful application of gesture recognition for
users who may not physically be able to use a
mouse or keyboard. Eye tracking in particular
may be of use for controlling cursor motion or
focusing on elements of a display.
Gesture recognition
Gesture recognition
1.Latency
Image processing can be significantly slow creating unacceptable latency for video
games and other similar applications.
2.Lack of Gesture Language
Different users make gestures differently, causing difficulty in identifying motions.
3.Robustness
Many gesture recognition systems do not read motions accurately or optimally due to
factors like insufficient background light, high background noise etc.
4.Performance
Image processing involved in gesture recognition is quite resource intensive and the
applications may found difficult to run on resource constrained devices.
Gesture recognition

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Gesture recognition

  • 2. Gestures are an important aspect of human interaction, both interpersonally and in the context of man-machine interfaces. A gesture is a form of non-verbal communication in which visible bodily actions communicate particular messages, either in place of speech or together and in parallel with words. Gestures include movement of the hands, face, or other parts of the body.
  • 3. Military air marshals use hand and body gestures to direct flight operations aboard aircraft carriers.
  • 4. Gesticulation:- Spontaneous movements of the hands and arms that accompany speech. Language-like gestures:- Gesticulation that is integrated into a spoken utterance, replacing a particular spoken word or phrase. Pantomimes:- Gestures that depict objects or actions, with or without accompanying speech. Emblems:- Familiar gestures such as V for victory, thumbs up, and assorted rude gestures. Sign languages.:- Linguistic systems, such as American Sign Language, which are well defined.
  • 5.  What is Gesture Recognition ? Interface with computers using gestures of the human body, typically hand movements. Gesture recognition is an important skill for robots that work closely with humans. Gesture recognition is especially valuable in applications involving interaction human/robot for several reasons.
  • 6. A child being sensed by a simple gesture recognition algorithm detecting hand location and movement.
  • 7. A basic working of the gesture recognition system
  • 8. Hand gesture recognition is one obvious way to create a useful, highly adaptive interface between machines and their users. Hand gesture recognition technology would allow for the operation of complex machines using only a series of finger and hand movements, eliminating the need for physical contact between operator and machine.
  • 9. Facial gesture recognition is another way of creating an effective non-contact interface between users and their machines. The goal of facial gesture recognition is for machines to effectively understand emotions and other communication cues within humans, regardless of the countless physical differences between individuals.
  • 10. Sign language recognition is one of the most promising sub-fields in gesture recognition research. Effective sign language recognition would grant the deaf and hard-of-hearing expanded tools for communicating with both other people and machines.
  • 11. Gesture Sensing Technologies:-  Device Gesture Technologies  Vision-based Technologies  Electrical Field Sensing Touch based gestures Non-Contact: Contact type:
  • 12.  Device-based techniques use a glove, stylus, or other position tracker, whose movements send signals that the system uses to identify the gesture.  The glove is equipped with a variety of sensors to provide information about hand position, orientation, and flex of fingers.
  • 13. There are two approaches to vision based gesture recognition: Model based techniques: They try to create a three dimensional model of the users hand and use this for recognition. Image based methods: Image-based techniques detect a gesture by capturing pictures of a user’s motions during the course of a gesture.
  • 14. Proximity of a human body or body part can be measured by sensing electric fields . These measurements can be used to measure the distance of a human hand or other body part from an object; this facilitates a vast range of applications for a wide range of industries.
  • 15. These can provide input to the computer about the position and rotation of the hands using magnetic or inertial tracking devices. The first commercially available hand- tracking glove-type device was the Data Glove , a glove-type device which could detect hand position, movement and finger bending. This uses fiber optic cables running down the back of the hand. Light pulses are created and when the fingers are bent, light leaks through small cracks and the loss is registered, giving an approximation of the hand pose. Wired gloves:-
  • 16. A Stereo camera is a camera that has two lenses about the same distance apart as your eyes and takes two pictures at the same time. This simulates the way we actually see and therefore creates the 3D effect when viewed. Using two cameras whose relations to one another are known, a 3D representation can be approximated by the output of the cameras. Stereo cameras:-
  • 18. Using specialized cameras such as structured light or time-of-flight cameras, one can generate a depth map of what is being seen through the camera at a short range, and use this data to approximate a 3d representation of what is being seen. These can be effective for detection of hand gestures due to their short range capabilities. Depth-aware cameras.
  • 20. Technology Behind It:- Thermal cameras: An infrared camera is a device that detects infrared radiation(temperature) from the target object and converts it into an electronic signal to generate a thermal picture on a monitor or to make temperature calculations on it. The temperature which is captured by an infrared camera can be measured or quantified exactly, so that not only the thermal behavior can be observed but also the relative magnitude of temperature related problems can be recognized and noted.
  • 22. These controllers act as an extension of the body so that when gestures are performed, some of their motion can be conveniently captured by software. Mouse gestures are one such example, where the motion of the mouse is correlated to a symbol being drawn by a person's hand, as is the Wii Remote, which can study changes in acceleration over time to represent gestures. Controller –based gestures:-
  • 23. A normal camera can be used for gesture recognition where the resources/environment would not be convenient for other forms of image- based recognition. Earlier it was thought that single camera may not be as effective as stereo or depth aware cameras, but a start-up based out of Palo Alto named Flutter is challenging this theory. It has released an app that could be downloaded to by any windows/mac computer with built-in webcam. Single camera:-
  • 24. 3D model-based algorithms Skeletal-based algorithms Appearance-based models
  • 25. 3D model-based algorithms:- A real hand (left) is interpreted as a collection of vertices and lines in the 3D mesh version (right), and the software uses their relative position and interaction in order to infer the gesture.Skeletal based algorithms:- The skeletal version (right) is effectively modelling the hand (left). This has fewer parameters than the volumetric version and it's easier to compute, making it suitable for real-time gesture analysis systems Appearance based models:- These binary silhouette(left) or contour(right) images represent typical input for appearance- based algorithms. They are compared with different hand templates and if they match, the correspondent gesture is inferred.
  • 26. Socially assistive robotics:- Sign language recognition:- By using proper sensors worn on the body of a patient and by reading the values from those sensors, robots can assist in patient rehabilitation. The best example can be stroke rehabilitation. Just as speech recognition can transcribe speech to text, certain types of gesture recognition software can transcribe the symbols represented through sign language into text.
  • 27. Virtual controllers:- Remote control:- Through the use of gesture recognition, remote control with the wave of a hand of various devices is possible. For systems where the act of finding or acquiring a physical controller could require too much time, gestures can be used as an alternative control mechanism. Controlling secondary devices in a car, or controlling a television set are examples of such usage.
  • 28. Control through facial gestures:- Immersive game technology:- Gestures can be used to control interactions within video games to try and make the game player's experience more interactive or immersive. Controlling a computer through facial gestures is a useful application of gesture recognition for users who may not physically be able to use a mouse or keyboard. Eye tracking in particular may be of use for controlling cursor motion or focusing on elements of a display.
  • 31. 1.Latency Image processing can be significantly slow creating unacceptable latency for video games and other similar applications. 2.Lack of Gesture Language Different users make gestures differently, causing difficulty in identifying motions. 3.Robustness Many gesture recognition systems do not read motions accurately or optimally due to factors like insufficient background light, high background noise etc. 4.Performance Image processing involved in gesture recognition is quite resource intensive and the applications may found difficult to run on resource constrained devices.