We propose a novel approach to tracking objects by low-level line correspondences. In our implementation we show that this approach is usable even when tracking objects with lack of texture, exploiting situations, when feature-based trackers fails due to the aperture problem. Furthermore, we suggest an approach to failure detection and recovery to maintain long-term stability. This is achieved by remembering configurations which lead to good pose estimations and using them later for tracking corrections. We carried out experiments on several sequences of different types. The proposed tracker proves itself as competitive or superior to state-of-the-art trackers in both standard and low-textured scenes.
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