Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
A Four-step Camera Calibration Procedure with Implicit Image Correction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Registration of Regions of Interest (ROI) in Video Sequences
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Comparison of Graph Cuts with Belief Propagation for Stereo, using Identical MRF Parameters
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Non-negative Matrix Factorization with Sparseness Constraints
The Journal of Machine Learning Research
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
A Roadmap to the Integration of Early Visual Modules
International Journal of Computer Vision
Mutual information based registration of multimodal stereo videos for person tracking
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
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In this paper, we propose a novel stereo method for registering foreground objects in a pair of thermal and visible videos of close-range scenes. In our stereo matching, we use Local Self-Similarity (LSS) as similarity metric between thermal and visible images. In order to accurately assign disparities to depth discontinuities and occluded Region Of Interest (ROI), we have integrated color and motion cues as soft constraints in an energy minimization framework. The optimal disparity map is approximated for image ROIs using a Belief Propagation (BP) algorithm. We tested our registration method on several challenging close-range indoor video frames of multiple people at different depths, with different clothing, and different poses. We show that our global optimization algorithm significantly outperforms the existing state-of-the art method, especially for disparity assignment of occluded people at different depth in close-range surveillance scenes and for relatively large camera baseline.