Real-Time Analysis of Human Body Parts and Gesture-Activity Recognition in 3D

Real-Time Analysis of Human Body Parts and Gesture-Activity Recognition in 3D

Burak Ozer (Princeton University, USA), Tiehan Lv (Princeton University, USA) and Wayne Wolf (Princeton University, USA)
DOI: 10.4018/978-1-59140-299-2.ch004
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This chapter focuses on real-time processing techniques for the reconstruction of visual information from multiple views and its analysis for human detection and gesture and activity recognition. It presents a review of the main components of three-dimensional visual processing techniques and visual analysis of multiple cameras, i.e., projection of three-dimensional models onto two-dimensional images and three-dimensional visual reconstruction from multiple images. It discusses real-time aspects of these techniques and shows how these aspects affect the software and hardware architectures. Furthermore, the authors present their multiple-camera system to investigate the relationship between the activity recognition algorithms and the architectures required to perform these tasks in real time. The chapter describes the proposed activity recognition method that consists of a distributed algorithm and a data fusion scheme for two and three-dimensional visual analysis, respectively. The authors analyze the available data independencies for this algorithm and discuss the potential architectures to exploit the parallelism resulting from these independencies.

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