Curve matching and stereo calibration
Image and Vision Computing
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Duals, Invariants, and the Recognition of Smooth Objects from their Occlucing Contours
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Judging Whether Multiple Silhouettes Can Come from the Same Object
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Order Structure, Correspondence, and Shape Based Categories
Shape, Contour and Grouping in Computer Vision
Motion from the frontier of curved surfaces
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Camera Network Calibration and Synchronization from Silhouettes in Archived Video
International Journal of Computer Vision
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Recovering epipolar geometry from images of smooth surfaces
Pattern Recognition and Image Analysis
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This paper presents a geometric approach to recognizing smooth objects from their outlines. We define a signature function that associates feature vectors with objects and baselines connecting pairs of possible viewpoints. Feature vectors, which can be projective, affine, or Euclidean, are computed using the planes that pass through a fixed baseline and are also tangent to the object's surface. In the proposed framework, matching a test outline to a set of training outlines is equivalent to finding intersections in feature space between the images of the training and the test signature functions. The paper presents experimental results for the case of internally calibrated perspective cameras, where the feature vectors are angles between epipolar tangent planes.