An Improved Algorithm of Hand-Gesture Recognition Based on Haar-Like Features and Adaboost
| Autor: | Youdong Ding, Hai Bo Pang |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Computer science
business.industry Improved algorithm ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION General Engineering Pattern recognition Image (mathematics) Haar-like features Dimension (vector space) Gesture recognition Principal component analysis Computer vision Artificial intelligence AdaBoost business Gesture |
| Zdroj: | Advanced Materials Research. :1238-1241 |
| ISSN: | 1662-8985 |
| DOI: | 10.4028/www.scientific.net/amr.588-589.1238 |
| Popis: | In this paper, we proposed an improved algorithm of hand-gesture recognition based on Haar-like features and Adaboost. Initial, we calculated the Haar-like features of hand-gesture images by integral image. Then, we used the principal components analysis method to reduce the dimension of Haar-like features. At last, an Adaboost classifier performed the hand-gesture recognition task with the hand-gesture features. A dataset with large hand gestures (12 types, 600 hand-gesture images) was built, including some large pose-angle (about 40 deg.) hand-gesture images. Our experiment results demonstrated that our method could effectively recognize different hand gesture, and the best appropriate N was 12. In addition, the average processing time of the proposed method was about 0.05 second for every image. |
| Databáze: | OpenAIRE |
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