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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.
| Autorius: | Jun Ohya, Junji Yamato, Akira Utsumi, |
| Serija: | The International Series in Video Computing |
| Leidėjas: | Springer New York |
| Išleidimo metai: | 2012 |
| Knygos puslapių skaičius: | 164 |
| ISBN-10: | 1461353467 |
| ISBN-13: | 9781461353461 |
| Formatas: | 235 x 155 x 10 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
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