Robust and Efficient Detection of Salient Convex Groups
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Space Requirements of Indexing Under Perspective Projections
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching 3-D Models to 2-D Images
International Journal of Computer Vision
Extracting Salient Curves from Images: An Analysis of the Saliency Network
International Journal of Computer Vision
Uncertainty Propagation in Model-Based Recognition
International Journal of Computer Vision
3-D to 2-D Pose Determination with Regions
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
Global Detection of Salient Convex Boundaries
International Journal of Computer Vision
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We discuss a strategy for visual recognition by forming groups of salient image features, and then using these groups to index into a data base to find all of the matching groups of model features. We discuss the most space efficient possible method of representing 3-D models for indexing from 2-D data, and show how to account for sensing error when indexing. We also present a convex grouping method that is robust and efficient, both theoretically and in practice. Finally, we combine these modules into a complete recognition system, and test its performance on many real images.