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| 人体行为识别特征提取方法综述 | |
| 引用本文： | 张会珍,刘云麟,任伟建,刘欣瑜.人体行为识别特征提取方法综述[J].吉林大学学报(信息科学版),2008,38(3):360-370. |
| 作者姓名： | 张会珍 刘云麟 任伟建 刘欣瑜 |
| 作者单位： | 1． 东北石油大学a． 电气信息工程学院; b． 黑龙江省网络化与智能控制重点实验室，黑龙江大庆163318; 2． 中国石化销售股份有限公司上海石油分公司信息管理处，上海200002 |
| 基金项目： | 黑龙江省自然科学基金资助项目( F2018004) |
| 摘 要： | 行为识别的过程很大程度上可以看作特征提取与分类器相结合，故特征提取方法的优劣直接影响最终识
别效果。与静态图像物体识别相比，视频中人体行为识别特征提取更易受到动态背景、采集设备运动、视角和
光照等因素影响人体，从而对研究人员的工作提出了很大挑战。为此，综合了近几年对行为识别特征提取系
统分类和不同类型行为识别特征提取方法以及常用行为识别数据库等领域研究的最新进展，探讨了目前研究
难点，阐述了与未来可能的研究发展方向。 |
| 关 键 词： | 计算机视觉 行为识别 特征提取 行为识别数据集 |
| 收稿时间： | 2019-11-13 |
Human Behavior Recognition Feature Extraction Method: A Survey |
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| ZHANG Huizhen,LIU Yunlin,REN Weijian,LIU Xinyu.Human Behavior Recognition Feature Extraction Method: A Survey[J].Journal of Jilin University:Information Sci Ed,2008,38(3):360-370. | |
| Authors: | ZHANG Huizhen LIU Yunlin REN Weijian LIU Xinyu |
| Institution: | 1a． School of Electrical Engineering ＆ Information; 1b． Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control，Northeast Petroleum University，Daqing 163318，China; 2． Information Management Office，Sinopec Marketing Shanghai Company，Shanghai 200002，China |
| Abstract: | The process of behavior recognition can be regarded as the combination of feature extraction and classifier to a large extent． Compared to static image object recognition，video feature extraction of human behavior recognition is more susceptible to such factors as dynamic background，acquisition device motion， perspective and illumination，so it poses great challenges to researchers． Based on the systematic classification of behavior recognition feature extraction，according to the different types of behavior recognition feature extraction methods and common behavior recognition database，the behavior recognition feature extraction is systematically classified to expound the latest research progress． And the current research difficulties and possible future research directions are discussed． |
| Keywords: | computer vision behavior recognition feature extraction behavior identification dataset |
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