Discriminative Exemplar Coding for Sign Language Recognition with Kinect
文献类型：期刊论文
| 作者 | Sun, Chao1; Zhang, Tianzhu1 ; Bao, Bing-Kun2; Xu, Changsheng1; Mei, Tao3
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| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
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| 出版日期 | 2013-10-01 |
| 卷号 | 43期号:5页码:1418-1428 |
| 关键词 | Discriminative exemplar coding Kinect sensor sign language recognition |
| 英文摘要 | Sign language recognition is a growing research area in the field of computer vision. A challenge within it is to model various signs, varying with time resolution, visual manual appearance, and so on. In this paper, we propose a discriminative exemplar coding (DEC) approach, as well as utilizing Kinect sensor, to model various signs. The proposed DEC method can be summarized as three steps. First, a quantity of class-specific candidate exemplars are learned from sign language videos in each sign category by considering their discrimination. Then, every video of all signs is described as a set of similarities between frames within it and the candidate exemplars. Instead of simply using a heuristic distance measure, the similarities are decided by a set of exemplar-based classifiers through the multiple instance learning, in which a positive (or negative) video is treated as a positive (or negative) bag and those frames similar to the given exemplar in Euclidean space as instances. Finally, we formulate the selection of the most discriminative exemplars into a framework and simultaneously produce a sign video classifier to recognize sign. To evaluate our method, we collect an American sign language dataset, which includes approximately 2000 phrases, while each phrase is captured by Kinect sensor with color, depth, and skeleton information. Experimental results on our dataset demonstrate the feasibility and effectiveness of the proposed approach for sign language recognition. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | VIDEO |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000324586700010 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/2839]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100191, Peoples R China 2.China Singapore Inst Digital Media, Singapore, Singapore 3.Microsoft Res Asia, Internet Media Grp, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Sun, Chao,Zhang, Tianzhu,Bao, Bing-Kun,et al. Discriminative Exemplar Coding for Sign Language Recognition with Kinect[J]. IEEE TRANSACTIONS ON CYBERNETICS,2013,43(5):1418-1428. |
| APA | Sun, Chao,Zhang, Tianzhu,Bao, Bing-Kun,Xu, Changsheng,&Mei, Tao.(2013).Discriminative Exemplar Coding for Sign Language Recognition with Kinect.IEEE TRANSACTIONS ON CYBERNETICS,43(5),1418-1428. |
| MLA | Sun, Chao,et al."Discriminative Exemplar Coding for Sign Language Recognition with Kinect".IEEE TRANSACTIONS ON CYBERNETICS 43.5(2013):1418-1428. |
入库方式： OAI收割
来源：自动化研究所
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