The document discusses gesture recognition systems, which allow humans to interact with machines through visible bodily motions or facial expressions. It describes how such systems work by capturing images of gestures via cameras, preprocessing the images, and identifying the gestures. Examples of applications mentioned include sign language recognition, game control through gestures, and using facial expressions for affective computing. Challenges with gesture recognition systems include the cost and difficulty of developing them, as each gesture must be assigned a specific command.

2. The ability of a computer to scan, store, and recognize human
gestures as the mode of interaction with machines.
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.

4. User
Normal User Physically Challenged
User
Perform Action
Gesture Recognition
System
Check for Errors
Conversion to Binary Image
Noise Removal
Resizing Picture
Conversion to Grayscale Image
Identify Gesture
Zooming in Binary Picture
Crop Image
«extend»
Update Background Picture
«include»
Web Cam
Capture Image
Transmit Image to System
«extend»
Locate Hand in Picture

5. Gesture Recognition System
Hand motion Recognition System
Face Recognition System
Iris Recognition System

6. In order to detect hand gesture, data about hand will have to be
collected.
A decision has to be made as to the nature and source of the data.
Two possible technologies to provide this information are:
1)A glove with sensor attached that measure the position of finger
joints.
2)An optical method (Hand)

7. KEYS:
a)Accelerometers
b)Data Board
c)Glove
d)Arm Tracker

13. Task of identify an already detected face as a known or unknown
face.
In more advance case “Telling exactly who’s face it is?”
Identify an object as a face and Decide if this face is
locate it in input image some one known or
unknown

16. Anger Fear Disgust Happy Sad Surprise

17. Iris recognition is an automated method
of biometric identification that uses mathematical
pattern-recognition techniques on video images of the
irises of an individual's eyes, whose complex random
patterns are unique and can be seen from some
distance.

21. 1. Sign language recognition
2. Directional indication through pointing.
3. Control through facial gestures
4. Immersive game technology
5. Affective computing.
6. Remote control.
7. Alternative computer interfaces

22. • The cost of implementation
• Such systems are difficult to develop as each
gesture is assigned a specific control
command, this system is not platform
independent since certain control commands
vary as the operating system varies.

23. • Control of consumer electronics
• Computer games
• Security System
• Television
• In ATM’s