计算机应用与软件2017，Vol.34Issue(2)：189-192,219,5.DOI:10.3969/j.issn.1000-386x.2017.02.033
利用深度视频中的关节运动信息研究人体行为识别
STUDY OF HUMAN ACTION RECOGNITION BY USING SKELETON MOTION INFORMATION IN DEPTH VIDEO
摘要
Abstract
Due to high computation overhead,little progress has been achieved in human action recognition (HAR) based on hand-crafted feature and RGB videos in recent years.Compared with RGB video,depth video sequence is able to extract geometry structural information of animated objects,it is also more insensitive to light changes and more discriminative in many vision tasks such as segmentation and activity recognition.Thus,an effective and straightforward HAR method by using joints motion information of the depth sequence is proposed.First,two feature vectors are extracted according to the human joints information in depth video to indicate the angle and position information among joints.Then,the obtained vectors are classified and identified by using Liblinear classifier.Finally,the action recognition result is achieved by fusing the classification results.The extracted features are view-invariant because the vectors contain only angle and relative position information among joints,they keep the same even though the angle of view is different.Experimental results demonstrate that the method has low computation overhead and performs comparable results on the UTKinect-Action3D dataset compared with state-of-the-art methods.关键词
深度学习/人体行为识别/深度视频/关节信息Key words
Deep learning/Human action recognition/Depth video/Skeleton information分类
信息技术与安全科学引用本文复制引用
刘智,董世都..利用深度视频中的关节运动信息研究人体行为识别[J].计算机应用与软件,2017,34(2):189-192,219,5.基金项目
国家自然科学基金项目(61202348) （61202348）
重庆市教委科学技术研究项目(KJ1400926). （KJ1400926）
