The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational geometry: a retrospective
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Computing Size Functions from Edge Maps
International Journal of Computer Vision
Uncertainty Propagation in Model-Based Recognition
International Journal of Computer Vision
Multidimensional Indexing for Recognizing Visual Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hi-index | 0.00 |
This thesis addresses the problem of recognizing solid objects in the three-dimensional world, using two-dimensional shape information extracted from a single image. Objects can be partly occluded and can occur in cluttered scenes. A model based approach is taken, where stored models are matched to an image. The matching problem is separated into two stages, which employ different representations of objects. The first stage uses the smallest possible number of local features to find transformations from a model to an image. This minimizes the amount of search required in recognition. The second stage uses the entire edge contour of an object to verify each transformation. This reduces the chance of finding false matches.