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Real time motion capture using a single time-of-flight camera
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Markerless tracking of human pose is a hard yet relevant problem. In this paper, we derive an efficient filtering algorithm for tracking human pose at 4-10 frames per second using a stream of monocular depth images. The key idea is to combine an accurate generative model-which is achievable in this setting using programmable graphics hardware-with a discriminative model that feeds datadriven evidence about body part locations. In each filter iteration, we apply a form of local model-based
doi:10.1109/cvpr.2010.5540141
dblp:conf/cvpr/GanapathiPKT10
fatcat:mqqf6xugffagbdqpi3pznzeicq