tracking, posture estimation and behavior recognition
Edición de la obra Analyzing video sequences of multiple humans
| Autor | Jun Ohya |
|---|---|
| Editorial | Springer |
| Fecha de publicación | 2002 |
| Lugar | Boston, MA |
| Idioma | inglés |
| Páginas | 160 |
| Formato | [electronic resource] |
| ISBN-13 | 9781461510031 |
| ISBN-10 | 1461510031 |
| OCLC | 840283568 |
| Serie | Kluwer international series in video computing -- 3 · Kluwer international series in video computing -- 3. |
| Número de Cutter | O38a |
|---|
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.