International Journal of Computer Vision
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Robust recognition using eigenimages
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Matching in Computer Vision Using Probabilistic Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Object Recognition by Geometric Hashing
ECCV '90 Proceedings of the First European Conference on Computer Vision
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Model-Based Object Recognition - A Survey of Recent Research
Model-Based Object Recognition - A Survey of Recent Research
Serial multiple classifier systems exploiting a coarse to fine output coding
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
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We propose an affine invariant object recognition system which is based on the principle of multiple classifier fusion. Accordingly, two recognition experts are developed and used in tandem. The first expert performs a course grouping of the object hypotheses based on an entropy criterion. This initial classification is performed using colour cues. The second expert establishes the object identity by considering only the subset of candidate models contained in the most probable coarse group. This expert takes into account geometric relations between object primitives and determines the winning hypothesis by means of relaxation labelling. We demonstrate the effectiveness of the proposed object recognition strategy on the Surrey Object Image Library database. The experimental results not only show improved recognition performance but also a computational speed up.