A novel approach for dynamic hand gesture recognition using contour-based similarity images
| Autor: | Farbod Razzazi, Alireza Behrad, Saeed Nasri |
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| Rok vydání: | 2014 |
| Předmět: |
Similarity (geometry)
American Sign Language InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g. HCI) business.industry Computer science Applied Mathematics ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-invariant feature transform language.human_language Motion (physics) Computer Science Applications Computational Theory and Mathematics Gesture recognition language Computer vision Artificial intelligence business Representation (mathematics) Gesture |
| Zdroj: | International Journal of Computer Mathematics. 92:662-685 |
| ISSN: | 1029-0265 0020-7160 |
| DOI: | 10.1080/00207160.2014.915958 |
| Popis: | A novel approach is proposed for the recognition of moving hand gestures based on the representation of hand motions as contour-based similarity images (CBSIs). The CBSI was constructed by calculating the similarity between hand contours in different frames. The input CBSI was then matched with CBSIs in the database to recognize the hand gesture. The proposed continuous hand gesture recognition algorithm can simultaneously divide the continuous gestures into disjointed gestures and recognize them. No restrictive assumptions were considered for the motion of the hand between the disjointed gestures. The proposed algorithm was tested using hand gestures from American Sign Language and the results showed a recognition rate of 91.3% for disjointed gestures and 90.4% for continuous gestures. The experimental results illustrate the efficiency of the algorithm for noisy videos. |
| Databáze: | OpenAIRE |
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