Analyzing Video Sequences of Multiple Humans Tracking, Posture Estimation and Behavior Recognition |
|
| Author:
| Ohya, Jun
Utsumi, Akira
Yamato, Junji |
| Series title: | The International Series in Video Computing Ser. |
| ISBN: | 978-1-4613-5346-1 |
| Publication Date: | Oct 2012 |
| Publisher: | Springer
|
| Book Format: | Paperback |
| List Price: | USD $169.99 |
Book Description:
|
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...
More DescriptionAnalyzing 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.