Cross-view Action Recognition via Transductive Transfer Learning
文献类型:会议论文
作者 | Jie Qin![]() ![]() |
出版日期 | 2013-09-15 |
会议日期 | 15-18 September 2013 |
会议地点 | Melbourne, Australia |
关键词 | Transductive Svm Action Recognition Transfer Learning |
英文摘要 | Human action recognition is a hot topic in computer vision field. Various applicable approaches have been proposed to recognize different types of actions. However, the recognition performance deteriorates rapidly when the viewpoint changes. Traditional approaches aim to address the problem by inductive transfer learning, in which target-view samples are manually labeled. In this paper, we present a novel approach for cross-view action recognition based on transductive transfer learning. We address the problem by transferring instances across views. In our settings, both labels of examples from the target view and the corresponding relation between examples from pairwise views are dispensable. Experimental results on the IXMAS multi-view data set demonstrate the effectiveness of our approach, and are comparable to the state of the art. |
会议录 | ICIP 2013
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源URL | [http://ir.ia.ac.cn/handle/173211/13286] ![]() |
专题 | 自动化研究所_智能感知与计算研究中心 |
通讯作者 | Zhaoxiang Zhang |
推荐引用方式 GB/T 7714 | Jie Qin,Zhaoxiang Zhang,Yunhong Wang. Cross-view Action Recognition via Transductive Transfer Learning[C]. 见:. Melbourne, Australia. 15-18 September 2013. |
入库方式: OAI收割
来源:自动化研究所
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