[1]王策,姬晓飞,李一波.一种简便的视角无关动作识别方法[J].智能系统学报,2014,9(05):577-583.[doi:10.3969/j.issn.1673-4785.201307057]
 WANG Ce,JI Xiaofei,LI Yibo.Study on a simple view-invariant action recognition method[J].CAAI Transactions on Intelligent Systems,2014,9(05):577-583.[doi:10.3969/j.issn.1673-4785.201307057]
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一种简便的视角无关动作识别方法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年05期
页码:
577-583
栏目:
出版日期:
2014-10-25

文章信息/Info

Title:
Study on a simple view-invariant action recognition method
作者:
王策 姬晓飞 李一波
沈阳航空航天大学 自动化学院, 辽宁 沈阳 110136
Author(s):
WANG Ce JI Xiaofei LI Yibo
School of Automation, Shenyang Aerospace University, Shenyang 110136, China
关键词:
动作识别视角无关视角空间切分兴趣点光流特征混合特征隐马尔可夫模型似然概率加权融合
Keywords:
action recognitionview-invariantview-space partitioninginterest pointsoptical flowmixed featurehidden Markov modellikelihood probability weighted fusion
分类号:
TP391.4
DOI:
10.3969/j.issn.1673-4785.201307057
摘要:
针对日常生活中人体执行动作时存在视角变化而导致难以识别的问题,提出一种基于视角空间切分的多视角空间隐马尔可夫模型(HMM)概率融合的视角无关动作识别算法。该方法首先按照人体相对于摄像机的旋转方向将视角空间分割为多个子空间,然后选取兴趣点视频段词袋特征与分区域的光流特征相融合,形成具有一定视角鲁棒性特征对人体运动信息进行描述,并在每个子视角空间下利用HMM建立各人体动作的模型,最终通过将多视角空间相应的动作模型似然概率加权融合,实现对未知视角动作的识别。利用多视角IXMAS动作识别数据库对该算法进行测试的实验结果表明,该算法实现简单且对未知视角下的动作具有较好识别结果。
Abstract:
It is difficult to recognize the human actions under view changes in daily living. In order to solve this problem, a novel multi-view space hidden Markov model algorithm for view-invariant action recognition based on view space partitioning is proposed in this paper. First, the whole view space is partitioned into multiple sub-view spaces according to the rotation direction of a person relative to camera. Next, a view-robust feature representation by combination of the bag of interest point words in shot length-based video and amplitude histogram of local optical flow is utilized for describing the information of human actions. Thereafter, the human action models in each sub-view space are trained by HMM algorithm. Finally, the unknown view action is recognized via the likelihood probability weighted fusion of the corresponding action models in multi-view space. The experimental results on multi-view action recognition dataset IXMAS demonstrated that the proposed approach is easy to implement and has satisfactory performance for the unknown view action recognition.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2013-07-30。
基金项目:国家自然科学基金资助项目(61103123).
作者简介:王策, 男, 1989年生, 硕士研究生, 主要研究方向为基于视频的人体运动建模及其分析;李一波, 男, 1963年生, 教授, 博士生导师, 博士, 主要研究方向为生物特征识别、图像处理与模式识别、飞行控制、复杂系统、人工智能等。曾获军队级科技进步3等奖1项、省国防工业办公室科技进步2等奖1项。主持和参与近30项科研项目, 发表学术论文100余篇, 其中被SCI及EI检索30余篇。
通讯作者:姬晓飞, 女, 1978年生, 副教授, 博士, 主要研究方向为视频分析与处理、模式识别。承担国家自然科学基金项目、教育部留学回国启动基金项目等多项基金研究工作。发表学术论文30余篇, 其中被SCI、EI检索15篇。参与编著英文专著1部。E-mail:jixiaofei7804@126.com.
更新日期/Last Update: 1900-01-01