Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance
<p/> <p>Efficient analysis of human behavior in video surveillance scenes is a very challenging problem. Most traditional approaches fail when applied in real conditions and contexts like amounts of persons, appearance ambiguity, and occlusion. In this work, we propose to deal with this...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2011-01-01
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| Series: | EURASIP Journal on Image and Video Processing |
| Online Access: | http://jivp.eurasipjournals.com/content/2011/163682 |
| _version_ | 1811326497780137984 |
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| author | Benabbas Yassine Ihaddadene Nacim Djeraba Chaabane |
| author_facet | Benabbas Yassine Ihaddadene Nacim Djeraba Chaabane |
| author_sort | Benabbas Yassine |
| collection | DOAJ |
| description | <p/> <p>Efficient analysis of human behavior in video surveillance scenes is a very challenging problem. Most traditional approaches fail when applied in real conditions and contexts like amounts of persons, appearance ambiguity, and occlusion. In this work, we propose to deal with this problem by modeling the global motion information obtained from optical flow vectors. The obtained direction and magnitude models learn the dominant motion orientations and magnitudes at each spatial location of the scene and are used to detect the major motion patterns. The applied region-based segmentation algorithm groups local blocks that share the same motion direction and speed and allows a subregion of the scene to appear in different patterns. The second part of the approach consists in the detection of events related to groups of people which are merge, split, walk, run, local dispersion, and evacuation by analyzing the instantaneous optical flow vectors and comparing the learned models. The approach is validated and experimented on standard datasets of the computer vision community. The qualitative and quantitative results are discussed.</p> |
| first_indexed | 2024-04-13T14:50:19Z |
| format | Article |
| id | doaj.art-0bc4643db60841c985527ab07a493f49 |
| institution | Directory Open Access Journal |
| issn | 1687-5176 1687-5281 |
| language | English |
| last_indexed | 2024-04-13T14:50:19Z |
| publishDate | 2011-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Image and Video Processing |
| spelling | doaj.art-0bc4643db60841c985527ab07a493f492022-12-22T02:42:36ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-51761687-52812011-01-0120111163682Motion Pattern Extraction and Event Detection for Automatic Visual SurveillanceBenabbas YassineIhaddadene NacimDjeraba Chaabane<p/> <p>Efficient analysis of human behavior in video surveillance scenes is a very challenging problem. Most traditional approaches fail when applied in real conditions and contexts like amounts of persons, appearance ambiguity, and occlusion. In this work, we propose to deal with this problem by modeling the global motion information obtained from optical flow vectors. The obtained direction and magnitude models learn the dominant motion orientations and magnitudes at each spatial location of the scene and are used to detect the major motion patterns. The applied region-based segmentation algorithm groups local blocks that share the same motion direction and speed and allows a subregion of the scene to appear in different patterns. The second part of the approach consists in the detection of events related to groups of people which are merge, split, walk, run, local dispersion, and evacuation by analyzing the instantaneous optical flow vectors and comparing the learned models. The approach is validated and experimented on standard datasets of the computer vision community. The qualitative and quantitative results are discussed.</p>http://jivp.eurasipjournals.com/content/2011/163682 |
| spellingShingle | Benabbas Yassine Ihaddadene Nacim Djeraba Chaabane Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance EURASIP Journal on Image and Video Processing |
| title | Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance |
| title_full | Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance |
| title_fullStr | Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance |
| title_full_unstemmed | Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance |
| title_short | Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance |
| title_sort | motion pattern extraction and event detection for automatic visual surveillance |
| url | http://jivp.eurasipjournals.com/content/2011/163682 |
| work_keys_str_mv | AT benabbasyassine motionpatternextractionandeventdetectionforautomaticvisualsurveillance AT ihaddadenenacim motionpatternextractionandeventdetectionforautomaticvisualsurveillance AT djerabachaabane motionpatternextractionandeventdetectionforautomaticvisualsurveillance |