ACADSTAFF UGM
| Title | : | Loitering Detection Using Spatial-Temporal Information for Intelligent Surveillance Systems on Vision Sensor |
| Author | : |
Wahyono, Ph.D. (1) Prof. Drs. Agus Harjoko, M.Sc., Ph.D. (2) Dr. Andi Dharmawan, S.Si., M.Cs. (3) Faisal Dharma Adhinata (4) Gamma Kosala (5) Prof. Kanghyun Jo (6) |
| Date | : | 22 2023 |
| Keyword | : | loitering detection,intelligent surveillance system,vision sensor,spatial information,temporal information,support vector machine,random forest,human detection and tracking loitering detection,intelligent surveillance system,vision sensor,spatial information,temporal information,support vector machine,random forest,human detection and tracking |
| Abstract | : | As one of the essential modules in intelligent surveillance systems, loitering detection play an important role in reducing theft incidents by analyzing human behavior. This paper introduced a novel strategy for detecting the loitering activities of humans in the monitoring area for an intelligent surveillance system based on sensor vision. The proposed strategy combined spatial and temporal information in the feature extraction stage to decide whether the human movement can be regarded as loitering. This movement has been previously tracked using human detectors and particle filter tracking. The proposed method has been evaluated using our dataset consisting of 20 videos. The experimental results show that the proposed method could achieve a relatively good accuracy of 85% when utilizing the random forest classifier in the decision stage. Thus, it could be integrated as one of the modules in the intelligence surveillance system. |
| Group of Knowledge | : | Ilmu Komputer |
| Original Language | : | English |
| Level | : | Internasional |
| Status | : |
Published
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| No | Title | Action |
|---|---|---|
| 1 |
202302-jsan-full-dokumenpdf.pdf
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