Phase-based disparity measurement
CVGIP: Image Understanding
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mapping a manifold of perceptual observations
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Robust classification of hand postures against complex backgrounds
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Recognition by Linear Combination of Models
Recognition by Linear Combination of Models
Learning the Topology of Object Views
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Revised Papers from the International Workshop on Sensor Based Intelligent Robots
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We here describe a view-based system for the pose-independent representation of objects without making reference to 3-D models. Input to the system is a collection of pictures covering the viewing sphere with no pose information being provided. We merge pictures into a continuous pose-parameterized coverage of the viewing sphere. This can serve as a basis for pose-independent recognition and for the reconstruction of object aspects from arbitrary pose. Our data format for individual pictures has the form of graphs labeled with Gabor jets. The object representation is constructed in two steps. Local aspect representations are formed from clusters of similar views related by point correspondences. Principal component analysis (PCA) furnishes parameters that can be mapped onto pose angles. A global representation is constructed by merging these local aspects.