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Gesture Recognition

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Prajwal C

on 7 November 2013

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Transcript of Gesture Recognition

Gesture Recognition
Introduction:
Problem Definition
"Introducing a system that aims at recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body"
Tools Used
Open CV
MATLAB

Open CV
The Open CV project was initially an Intel Research initiative to advance CPU-intensive applications, part of a series of projects including real-time ray tracing and 3D display walls.
Advance vision-based commercial applications by making portable, performance-optimized code available for free with a license that did not require to be open or free themselves.
Programming language for Open CV
OpenCV is written in C++ and its primary interface is in C++, but it still retains a less comprehensive though extensive older C interface.
There are now full interfaces in Python, Java and MATLAB/OCTAVE.


Gesture Recognition:
An Overview
Gestures are expressive, meaningful body motions involving physical movements of the fingers, hands, arms, face, or body with the intent of:
1. Conveying meaningful information or
2. Interacting with the environment
Types of gesture recognition
Broad classification of gesture recognition is as follows:
1. Hand and arm gestures: recognition of hand poses, sign languages, and entertainment applications
2. Head and face gestures: some examples are: a)nodding or shaking of head; b) direction of eye gaze; c) raising the eyebrows; d) opening the mouth to speak;
3. Body gestures: involvement of full
Matlab
MATLAB is a high-performance language for technical computing.
Prior Art
Face Detection
To identify and detect the
presence of Human face

Feature Extraction
Skin segmentation
To identify and select region of possible human skin tone

Active Contours
Snakes, and other algorithms are used to detect the boundaries of images present in the foreground.

Feature Selection
The optimization process used to make computation faster, suitable for video processing and gesture recognition.

Existing Techniques
HMM
Virtual (hence, 'hidden’) points are used to track the motion of the hand.


It is a mathematical model based on spatial probability
Baum–Welch algorithm and Viterbi algorithm are used for training and decoding respectively.
FSM
Condensation Algorithm
Mathematical model of computation.
Tracks transition between two events.
A gesture is modelled as a ordered sequence of states, and the gesture is recognized by prototype trajectory.

Based on particle filtering, tracking rapid motion of objects.
Representation of probabilities by samples.

Applications
Virtual reality —Interactive virtual worlds
—Games
—Virtual studios
—Character animation
—Teleconferencing
“Smart” surveillance systems —Access control
—Parking lots
—Supermarkets, department stores
—Vending machines, ATMs
Advanced user interfaces —Social interfaces
—Sign-language translation
—Gesture driven control
—Signaling in high-noise environments
(airports, factories)
Motion analysis —Content-based indexing of sports video
footage
—Personalized training in golf, tennis, etc.
—Choreography of dance and ballet.
Presentations can be done using gesture controlled slides.
High-security surveillance: certain movements of assassins might help predict an assassination before it happens/ or a terrorist.
Blind people will be able to perform simple tasks on a computer by using gestures. It can also be used to decipher sign language and also make HCI (human-computer interaction) language independent.
Interactive learning platform for young children.
Monitoring and identifying emotional states in patients, alertness of automobile drivers/pilots ,etc.
Scope for future work:
Recognize not only hand gestures but expressions and body language as well.
It integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation.
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