Simultaneous Tracking and Estimation of a Skeletal Model for Monitoring Human Motion
نویسندگان
چکیده
This paper presents a vision system for tracking a 3D articulated human model from the observation of isolated features from multiple viewpoints. A generic model is instantiated by estimating invariant elements (limb lengths) during tracking. The model is used as feedback both in the estimation module for filtering and in the segmentation module where it predicts the feature’s position and size. Filtering is carried out with a Kalman filter with improved numerical stability using Joseph’s implementation. The robustness of this implementation is compared to the basic formulation on real sequences. Results demonstrate a rapid convergence of the filtered parameters despite large observation variances.
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