Estimation of human orientation in images captured with a range camera
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
A review on vision techniques applied to Human Behaviour Analysis for Ambient-Assisted Living
Expert Systems with Applications: An International Journal
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The knowledge about the body orientation of humans can improve speed and performance of many service components of a smart-room. Since many of such components run in parallel, an estimator to acquire this knowledge needs a very low computational complexity. In this paper we address these two points with a fast and efficient algorithm using the smart-room's multiple camera output. The estimation is based on silhouette information only and is performed for each camera view separately. The single view results are fused within a Bayesian filter framework. We evaluate our system on a subset of videos from the CLEAR 2007 dataset and achieve an average correct classification rate of 87.8%, while the estimation itself just takes 12 ms when four cameras are used.