Gesture recognition approach based on learning sparse representation
An approach of robust accelerometer-based hand gesture recognition based on self-learning sparse representa-tion was proposed. This method operated directly on the original acceleration signals by sparse representation without feature extraction and used the class-specific dictionary learning for sp...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2013-06-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436X.2013.06.016/ |
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| _version_ | 1841539828480475136 |
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| author | Ling XIAO Ren-fa LI Fan-zai ZENG Wei-lan QU |
| author_facet | Ling XIAO Ren-fa LI Fan-zai ZENG Wei-lan QU |
| author_sort | Ling XIAO |
| collection | DOAJ |
| description | An approach of robust accelerometer-based hand gesture recognition based on self-learning sparse representa-tion was proposed. This method operated directly on the original acceleration signals by sparse representation without feature extraction and used the class-specific dictionary learning for sparse modeling to reduce the computing cost and time of recognition. The proposed system can easily add a novel gesture category as well as remove existing ones. Ex-periments on real-world database of 18 hand gestures validate the availability of the proposed algorithm. |
| format | Article |
| id | doaj-art-a6d1c463c33d4c75a88bf9c82225429c |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2013-06-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-a6d1c463c33d4c75a88bf9c82225429c2025-01-14T06:35:34ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2013-06-013412813559673011Gesture recognition approach based on learning sparse representationLing XIAORen-fa LIFan-zai ZENGWei-lan QUAn approach of robust accelerometer-based hand gesture recognition based on self-learning sparse representa-tion was proposed. This method operated directly on the original acceleration signals by sparse representation without feature extraction and used the class-specific dictionary learning for sparse modeling to reduce the computing cost and time of recognition. The proposed system can easily add a novel gesture category as well as remove existing ones. Ex-periments on real-world database of 18 hand gestures validate the availability of the proposed algorithm.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436X.2013.06.016/hand gesture recognitionsparse representationdictionary learningaccelerometer |
| spellingShingle | Ling XIAO Ren-fa LI Fan-zai ZENG Wei-lan QU Gesture recognition approach based on learning sparse representation Tongxin xuebao hand gesture recognition sparse representation dictionary learning accelerometer |
| title | Gesture recognition approach based on learning sparse representation |
| title_full | Gesture recognition approach based on learning sparse representation |
| title_fullStr | Gesture recognition approach based on learning sparse representation |
| title_full_unstemmed | Gesture recognition approach based on learning sparse representation |
| title_short | Gesture recognition approach based on learning sparse representation |
| title_sort | gesture recognition approach based on learning sparse representation |
| topic | hand gesture recognition sparse representation dictionary learning accelerometer |
| url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436X.2013.06.016/ |
| work_keys_str_mv | AT lingxiao gesturerecognitionapproachbasedonlearningsparserepresentation AT renfali gesturerecognitionapproachbasedonlearningsparserepresentation AT fanzaizeng gesturerecognitionapproachbasedonlearningsparserepresentation AT weilanqu gesturerecognitionapproachbasedonlearningsparserepresentation |