A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
How Easy is Matching 2D Line Models Using Local Search?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Multiscale Categorical Object Recognition Using Contour Fragments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust online appearance models for visual tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic target recognition by matching oriented edge pixels
IEEE Transactions on Image Processing
An adaptive coupled-layer visual model for robust visual tracking
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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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.