Analyzing Video Sequences of Multiple Humans
Produktnummer:
18883da6bca4ac49ee9635dc1c21658e7d
| Autor: | Ohya, Jun Utsumi, Akira Yamato, Junji |
|---|---|
| Themengebiete: | 3D Virtual Environments Virtual Reality algorithms computer graphics computer vision graphics image processing pattern recognition video |
| Veröffentlichungsdatum: | 31.03.2002 |
| EAN: | 9781402070211 |
| Sprache: | Englisch |
| Seitenzahl: | 138 |
| Produktart: | Gebunden |
| Verlag: | Springer US |
| Untertitel: | Tracking, Posture Estimation and Behavior Recognition |
Produktinformationen "Analyzing Video Sequences of Multiple Humans"
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.
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