Robust 3D visual tracking using particle filtering on the special Euclidean group: A combined approach of keypoint and edge features
作者： Changhyun Choi , Henrik I Christensen
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摘要: We present a 3D model-based visual tracking approach using edge and keypoint features in a particle filtering framework. Recently, particle-filtering-based approaches have been proposed to integrate multiple pose hypotheses and have shown good performance, but most of the work has made an assumption that an initial pose is given. To ameliorate this limitation, we employ keypoint features for initialization of the filter. Given 2D–3D keypoint correspondences, we randomly choose a set of minimum correspondences to calculate a …
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