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2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)最新文献

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A new approach to speed up in action recognition based on key-frame extraction 一种基于关键帧提取的动作识别新方法
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779982
Neda Azouji, Z. Azimifar
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引用次数: 5
Using optical flow and spectral clustering for behavior recognition and detection of anomalous behaviors 利用光流和光谱聚类进行行为识别和异常行为检测
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779980
A. Feizi, A. Aghagolzadeh, Hadi Seyedarabi
{"title":"Using optical flow and spectral clustering for behavior recognition and detection of anomalous behaviors","authors":"A. Feizi, A. Aghagolzadeh, Hadi Seyedarabi","doi":"10.1109/IRANIANMVIP.2013.6779980","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6779980","url":null,"abstract":"In this paper we propose an efficient method for behavior recognition and identification of anomalous behavior in video surveillance data. This approach consists of two phases of training and testing. In the training phase, first, we use background subtraction method to extract the moving pixels. Then optical flow vectors are extracted for moving pixels. We propose behavior features of each pixel as the average all optical flow vectors in the pixel over several frames in video data. Next, we use spectral clustering to classify behaviors wherein pixels that have similar behavior features are clustered together. Then we obtain a behavior model for each cluster using the normal distribution of the samples. Once the behavior models are obtained, in the testing phase, we use these models to detect anomalous behavior in a test video of the same scene. Experimental results on video surveillance sequences show the effectiveness and speed of proposed method.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125277096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Real time occlusion handling using Kalman Filter and mean-shift 使用卡尔曼滤波和均值移位的实时遮挡处理
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780003
R. Panahi, I. Gholampour, M. Jamzad
{"title":"Real time occlusion handling using Kalman Filter and mean-shift","authors":"R. Panahi, I. Gholampour, M. Jamzad","doi":"10.1109/IRANIANMVIP.2013.6780003","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6780003","url":null,"abstract":"Tracking objects using Mean Shift algorithm fails when there is a full/partial occlusion or when the background color and the desired object are close. In this paper we proposed a method using Kalman Filter and Mean Shift for handling these situations. Using similarity measure of Mean Shift algorithm we are able to detect an occlusion. Kalman Filter comes into the play for occlusion handling in a Buffer-Mode Process. We implemented this algorithm both on PC and DSP 64x+ Texas Instrument and the results are both tabulated. The results reveal the ability of our method to locate the object soon after occlusion disappearance.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"233 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114992294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
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