Bootstrapping the Condensation Algorithm
نویسندگان
چکیده
In model-based tracking the problem of a high dimensional solution space often appears. The standard solution to this problem is to use a prediction followed by an iterative search or a Kalman filter. The drawback of both is the risk of ending up in a local extremum. In this paper we suggest to apply bootstrapping to increase performance in model-based tracking. The bootstrapping information is in the form of the position of the hand in the image. The idea of bootstrapped tracking is exemplified in the context of monocular tracking of the 3D pose of a human arm utilising the Condensation algorithm. A number of tests are conducted and it is concluded that bootstrapped tracking is a promising approach when solving some of the inherent problems in model-based tracking.
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