The International Series in Video Computing: Tracking, Posture Estimation and Behavior Recognition

Ohya, Jun; Utsumi, Akira; Yamato, Junji

Analyzing Video Sequences of Multiple Humans: Tracking, Posture Estimation and Behavior Recognition describes some computer vision-based methods that analyze video sequences of humans. More specifically, methods for tracking multiple humans in a scene, estimating postures of a human body in 3D in real-time, and recognizing a person's behavior (gestures or activities) are discussed. For the tracking algorithm, the authors developed a non-synchronous method that tracks multiple persons by exploiting a Kalman filter that is applied to multiple video sequences. For estimating postures, an algorithm is presented that locates the significant points which determine postures of a human body, in 3D in real-time. Human activities are recognized from a video sequence by the HMM (Hidden Markov Models)-based method that the authors pioneered. The effectiveness of the three methods is shown by experimental results.

Details

Published by: Springer

Publication Date: 2002-03-31

Format: Hardcover

ISBN-13: 9781402070211

DOI: 10.1007/978-1-4615-1003-1

Dimensions: 235cm x155cm

Pages: 138