||Reinbacher Christian, Rüther Matthias, Bischof Horst
||Computer Vision Winter Workshop
||We address the problem of model-based pose estimation from image sequences. While most methods build on local features, we use object silhou- ettes only, which are weaker, but considerably more robust cues. Without initialization of the pose, we are able to track the pose of rigid models through a video sequence, despite varying texture, illumination and appearance. Additionally our method handles multi- ple objects inherently and jointly estimates pose and object type. The method works at interactive frame rates, which makes it an ideal tool for augmented reality applications, active inspection systems and robotic manipulation tasks.
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