Shape-Based Mutual Segmentation
International Journal of Computer Vision
Robust feature point matching by preserving local geometric consistency
Computer Vision and Image Understanding
Dense and Deformable Motion Segmentation for Wide Baseline Images
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Nonlocal Similarity Image Filtering
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Simultaneous plane extraction and 2D homography estimation using local feature transformations
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Good match exploration using triangle constraint
Pattern Recognition Letters
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We present a technique to adapt the domain of local features through the matching process to augment their discriminative power. We start with local affine features selected and normalized independently in training and test images, and jointly expand their domain as part of the correspondence process, akin to a (non-rigid) registration task that yields a (multi-view) segmentation of the object of interest from clutter, including the detection of occlusions. We show how our growth process can be used to validate putative affine matches, to match a given "template" (an image of an object without clutter) to a cluttered and partially occluded image, and to match two images that contain the same unknown object in different clutter under different occlusions (unsupervised object detection).