Hand pose recognition using curvature scale space
| Autor: | Chin-Chen Chang, Yea-Shuan Huang, I-Yen Chen |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Physics::Computational Physics
business.industry Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Curvature scale space Nearest neighbour Pattern recognition Astrophysics::Cosmology and Extragalactic Astrophysics ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Computer vision Artificial intelligence Invariant (mathematics) business Computer Science::Information Theory Mathematics |
| Zdroj: | ICPR (2) |
| DOI: | 10.1109/icpr.2002.1048320 |
| Popis: | We present a feature extraction approach based on curvature scale space (CSS) for translation, scale, and rotation invariant recognition of hand poses. First, the CSS images are used to represent the shapes of boundary contours of hand poses. Then, we extract the multiple sets of CSS features to overcome the problem of deep concavities in contours of hand poses. Finally, nearest neighbour techniques are used to perform CSS matching between the multiple sets of input CSS features and the stored CSS features for hand pose identification. Results show the proposed approach can extract the multiple sets of CSS features from the input images and perform well for recognition of hand poses. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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