In this paper, we propose a method for detection and tracking of multiple planes in sequences of Time of Flight (ToF) depth images. Our approach extends the recent J-linkage algorithm for estimation of multiple model instances in noisy data to tracking. Instead of randomly selecting plane hypotheses in every image, we propagate plane hypotheses through the sequence of images, resulting in a significant reduction of computational load in every frame. We also introduce a multi-pass scheme that allows detecting and tracking planes of varying spatial extent along with their boundaries. Our qualitative and quantitative evaluation shows that the proposed method can robustly detect planes and consistently track the hypotheses through sequences of ToF images.
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