Abstract
We present a multi-camera system for recovering skeleton body pose, by performing real-time volume reconstruction and using a hierarchical stochastic pose search algorithm. Different from many multi-camera systems that require a few connected workstations, our system only uses a signle PC to control 8 cameras for synchronous image acquisition. Silhouettes of the 8 cameras are extracted via a color-based background subtraction algorithm, and set as input to the 3D volume reconstruction. Our system can perform real-time volume reconstruction rendered in point clouds, voxels as well as voxels with texturing. The full-body skeleton pose (29-D vector) is then recovered by fitting an articulated body model to the volume sequences. The pose estimation is performed in a hierarchical manner, by using a particle swarm optmization (PSO) based search strategy combined with soft constraints. 3D distance transform (DT) is used for reducing the computing time of objective evaluations.
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Zhang, Z., Seah, H.S., Quah, C.K., Ong, A., Jabbar, K. (2011). A Multiple Camera System with Real-Time Volume Reconstruction for Articulated Skeleton Pose Tracking. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17832-0_18
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DOI: https://doi.org/10.1007/978-3-642-17832-0_18
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