Abstract
In this paper, a novel shape classification technique based on a hierarchical shape representation and the back-propagation through structure (BPTS) learning algorithm is proposed. In our representation scheme, a shape is hierarchically represented with the segments composing the contour of the shape by using a scale-space filtering method. The BPTS algorithm is then applied to learn to classify shapes with such a tree-structure representation. Simulations on both artificially generated shape patterns and real world gesture patterns show that robust classification results can be achieved by using a small set of features only.
Original language | English |
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Title of host publication | ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing |
Subtitle of host publication | Computational Intelligence for the E-Age |
Publisher | IEEE |
Pages | 134-138 |
Number of pages | 5 |
Volume | 1 |
ISBN (Electronic) | 9789810475246, 9810475241 |
DOIs | |
Publication status | Published - 1 Jan 2002 |
Event | 9th International Conference on Neural Information Processing, ICONIP 2002 - Orchid Country Club, Singapore, Singapore Duration: 18 Nov 2002 → 22 Nov 2002 |
Conference
Conference | 9th International Conference on Neural Information Processing, ICONIP 2002 |
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Country/Territory | Singapore |
City | Singapore |
Period | 18/11/02 → 22/11/02 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
- Signal Processing