By Jun Ohya, Akira Utsumi, Junji Yamato
Analyzing Video Sequences of a number of people: monitoring, Posture Estimation and behaviour Recognition describes a few machine vision-based tools that examine video sequences of people. extra particularly, tools for monitoring a number of people in a scene, estimating postures of a human physique in 3D in real-time, and spotting a person's habit (gestures or actions) are mentioned. For the monitoring set of rules, the authors built a non-synchronous procedure that tracks a number of people by means of exploiting a Kalman filter out that's utilized to a number of video sequences. For estimating postures, an set of rules is gifted that locates the numerous issues which ensure postures of a human physique, in 3D in real-time. Human actions are well-known from a video series by means of the HMM (Hidden Markov Models)-based approach that the authors pioneered. The effectiveness of the 3 equipment is proven by means of experimental results.
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Additional resources for Analyzing Video Sequences of Multiple Humans: Tracking, Posture Estimation and Behavior Recognition
Example text
10. 10, bottom). , 1996]. cQ. camera n • ------ • feature point ......... ~. h 1 (t= fa) ~~"i ~\ / N(Xx"tb,Px"tb) ! ,.. \·..... h 1 (t=lt b ;········· . / ······-/ho(t= t a ) \· · · · ~. h·~~6·:·····t b) \ '\, . camera feature point • Una.. plan. 11. 3. ANALYZING VIDEO SEQUENCES OF MULTIPLE HUMANS Feature Matching at an Observation Node Let us consider the case illustrated in Fig. 11. Here, we assumed that the observation for camera l took place at time t a and the observation for camera m took place at time tb (t a < tb).
Note that the method in this section uses an infrared camera so as to facilitate the extraction of the human silhoutte at each frame. 4, noninfrared color CCD cameras can be used instead, as long as the silhouettes can be extracted from the background based on color alone. Before the processing of the image frames for the computation of the pose parameters, the initial frame needs to be calibrated. During the calibration, the person needs to keep the posture shown in Fig. 1, standing upright and keeping both arms horizontal.
In SPIE proceeding vol. 2615, pages 8998. Yamamoto, M. and Koshikawa, K. (1991). Human motion analysis based on a robot arm model. In Proc. of Computer Vision and Pattern Recognition, pages 664-665. -W. -H. (1997). Recursive resolving algorithm for multiple stereo and motion matches. Image and Vision Computing, 15:181-196. Chapter 3 POSTURE ESTIMATION lun Ohya Waseda University Global Information and Telecommunication Institute Bldg. 29-7,1-3-10 Nishi-Waseda, Shinjuku-ku, Tokyo 169-0051, Japan Abstract This chapter describes our real-time methods for locating significant points on the human body to determine posture.