{"title":"Intelligent detection of the falls in the elderly using fuzzy inference system and video-based motion estimation method","authors":"K. Rezaee, J. Haddadnia, A. Delbari","doi":"10.1109/IRANIANMVIP.2013.6779996","DOIUrl":null,"url":null,"abstract":"Automatic detection of the abnormal walking in people, especially such accidents as the falls in the elderly, based on image processing techniques and computer vision can help develop an efficient system that its implementation in various contexts enables us to monitor people's movements. This paper proposes a new algorithm, which drawing on fuzzy rules in classification of movements as well as the implementation of the motion estimation, allows the rapid processing of the input data. At the testing stage, 57425 video frames received from Mother Nursing Home in Farzanegan and the video sequences containing the falls of the elderly were used. The results show that the values of average accuracy (AAC), detection rate (DR) and false alarm rate (FAR) were at an acceptable level, respectively with 93%, 89% and 5%. Compared to the similar techniques, the implementation of the proposed system in nursing homes and residential areas allow the real time and intelligent monitoring of the people.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRANIANMVIP.2013.6779996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Automatic detection of the abnormal walking in people, especially such accidents as the falls in the elderly, based on image processing techniques and computer vision can help develop an efficient system that its implementation in various contexts enables us to monitor people's movements. This paper proposes a new algorithm, which drawing on fuzzy rules in classification of movements as well as the implementation of the motion estimation, allows the rapid processing of the input data. At the testing stage, 57425 video frames received from Mother Nursing Home in Farzanegan and the video sequences containing the falls of the elderly were used. The results show that the values of average accuracy (AAC), detection rate (DR) and false alarm rate (FAR) were at an acceptable level, respectively with 93%, 89% and 5%. Compared to the similar techniques, the implementation of the proposed system in nursing homes and residential areas allow the real time and intelligent monitoring of the people.