Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Reconstruction from Graphs Labeled with Responses of Gabor Filters
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Robust classification of hand postures against complex backgrounds
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Hi-index | 0.00 |
We introduce an object recognition system (called ORASSYLL) in which objects are represented as a sparse and spatially organized set of local (bent) line segments. The line segments correspond to binarized Gabor wavelets or banana wavelets, which are bent and stretched Gabor wavelets. These features can be metrically organized, the metric enables an effcient learning of object representations. Learning can be performed autonomously by utilizing motor-controlled feedback. The learned representation are used for fast and effcient localization and discrimination of objects in complex scenes. ORASSYLL has been heavily influenced by an older and well known vision system [4, 9], and has also been influenced by Biederman's comments to this older system [1]. A comparison of ORASSYLL and the older system, including some remarks about the specific role of Gabor wavelets within ORASSYLL, is given at the end of the paper.