Sequentially Supervised Long Short-Term Memory for Gesture Recognition
Wang, Peisong; Song, Qiang; Han, Hua; Cheng, Jian
发表期刊COGNITIVE COMPUTATION
2016-10-01
卷号8期号:5页码:982-991
文章类型Article
摘要Gesture recognition has been suffering from long-term dependencies and complex variations in both spatial and temporal dimensions. Many traditional methods use hand cropping and sliding window scheme in the spatial and temporal space, respectively. In this paper, we propose a sequentially supervised long short-term memory architecture, which allows using pose information to guide the learning process of gesture recognition using variable length inputs. Technically, we add supervision at each frame using human joint positions. Our proposed methods can solve gesture recognition and pose estimation problems simultaneously using only RGB videos without hand cropping. Experimental results on two benchmark datasets demonstrate the effectiveness of the proposed framework compared with the state-of-the-art methods.
关键词Gesture Recognition Pose Estimation Lstm Sequential Classification
WOS标题词Science & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1007/s12559-016-9388-6
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61332016) ; Project of Chinese Academy of Sciences(XDB02060001)
WOS研究方向Computer Science ; Neurosciences & Neurology
WOS类目Computer Science, Artificial Intelligence ; Neurosciences
WOS记录号WOS:000386351500018
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被引频次:16[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/13327
专题紫东太初大模型研究中心_图像与视频分析
作者单位Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
第一作者单位中国科学院自动化研究所
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Wang, Peisong,Song, Qiang,Han, Hua,et al. Sequentially Supervised Long Short-Term Memory for Gesture Recognition[J]. COGNITIVE COMPUTATION,2016,8(5):982-991.
APA Wang, Peisong,Song, Qiang,Han, Hua,&Cheng, Jian.(2016).Sequentially Supervised Long Short-Term Memory for Gesture Recognition.COGNITIVE COMPUTATION,8(5),982-991.
MLA Wang, Peisong,et al."Sequentially Supervised Long Short-Term Memory for Gesture Recognition".COGNITIVE COMPUTATION 8.5(2016):982-991.
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