液晶与显示2017，Vol.32Issue(9)：748-754,7.DOI:10.3788/YJYXS20173209.0748
基于局部块模型的复杂场景行为识别算法
Action recognition algorithm under complex scenes based on local part model
摘要
Abstract
In order to solve the accuracy of the action recognition system in complex scenes,an im-proved method based on local part model,feature pre-processing and feature generalization is pro-posed.The algorithm is based on the bag of the visual words.Local part model and random sampling are used to extract features.The redundance of the features and the relationship between the features are reduced by the pre-processed procedure.The features processed are closer to the original features, meanwhile the features are generalized to prevent the over fitting.To demonstrate the performance of the proposed method,experiments are carried on HMDB51 datasets.The results show that the algo-rithm has higher efficiency than the original in complex environment.Compared with other methods, the proposed algorithm shows more accurate.It has a better recognition effect on video sets with large volume,complex background and real scene.关键词
行为识别/视觉词袋模型/局部块模型/特征预处理/特征泛化处理Key words
action recognition/bag of the visual words/local part model/feature pre-processing/fea-ture generalization分类
信息技术与安全科学引用本文复制引用
周英姿,王正勇,卿粼波,何小海..基于局部块模型的复杂场景行为识别算法[J].液晶与显示,2017,32(9):748-754,7.基金项目
成都市科技惠民项目(No.2015-HM01-00293-SF) （No.2015-HM01-00293-SF）
特殊环境机器人技术四川省重点实验室开放基金(No.14zxtk03) （No.14zxtk03）
国家自然科学基金委员会和中国工程物理研究院联合基金(No.11176018) Supported by the Technology Program of Public Wellbeing of Chengdu(No.2015-HM01- 00293-SF) （No.11176018）
the Open Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan Province (No. 14zxtk03) （No. 14zxtk03）
National Natural Science Foundation of China(No.11176018) （No.11176018）
