Analyzing Video Sequences of Multiple Humans
Author | : Jun Ohya |
Publisher | : Springer Science & Business Media |
Total Pages | : 155 |
Release | : 2012-12-06 |
ISBN-10 | : 9781461510031 |
ISBN-13 | : 1461510031 |
Rating | : 4/5 (31 Downloads) |
Book excerpt: 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.