An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering
At present, traditional visual-based surveillance systems are becoming impractical, inefficient, and time-consuming. Automation-based surveillance systems appeared to overcome these limitations. However, the automatic systems have some challenges such as occlusion and retaining images smoothly and c...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/4/4/27 |
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| author | Liang Cheng Chang Shreya Pare Mahendra Singh Meena Deepak Jain Dong Lin Li Amit Saxena Mukesh Prasad Chin Teng Lin |
| author_facet | Liang Cheng Chang Shreya Pare Mahendra Singh Meena Deepak Jain Dong Lin Li Amit Saxena Mukesh Prasad Chin Teng Lin |
| author_sort | Liang Cheng Chang |
| collection | DOAJ |
| description | At present, traditional visual-based surveillance systems are becoming impractical, inefficient, and time-consuming. Automation-based surveillance systems appeared to overcome these limitations. However, the automatic systems have some challenges such as occlusion and retaining images smoothly and continuously. This research proposes a weighted resampling particle filter approach for human tracking to handle these challenges. The primary functions of the proposed system are human detection, human monitoring, and camera control. We used the codebook matching algorithm to define the human region as a target and track it, and we used the practical filter algorithm to follow and extract the target information. Consequently, the obtained information was used to configure the camera control. The experiments were tested in various environments to prove the stability and performance of the proposed system based on the active camera. |
| first_indexed | 2024-03-10T15:46:44Z |
| format | Article |
| id | doaj.art-70e8f7e6364f46cead468a5258919584 |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-10T15:46:44Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-70e8f7e6364f46cead468a52589195842023-11-20T16:25:11ZengMDPI AGBig Data and Cognitive Computing2504-22892020-10-01442710.3390/bdcc4040027An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle FilteringLiang Cheng Chang0Shreya Pare1Mahendra Singh Meena2Deepak Jain3Dong Lin Li4Amit Saxena5Mukesh Prasad6Chin Teng Lin7Department of Computer Science, National Chiao Tung University, Hsinchu 30010, TaiwanSchool of Computer Science, FEIT, University of Technology Sydney, Sydney 2007, AustraliaSchool of Computer Science, FEIT, University of Technology Sydney, Sydney 2007, AustraliaInstitute of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaDepartment of Electrical Engineering, National Taiwan Ocean University, Keelung 202301, TaiwanDepartment of Computer Science and Information Technology, Guru Ghasidas University, Bilaspur, Chhattisgarh 495009, IndiaSchool of Computer Science, FEIT, University of Technology Sydney, Sydney 2007, AustraliaSchool of Computer Science, FEIT, University of Technology Sydney, Sydney 2007, AustraliaAt present, traditional visual-based surveillance systems are becoming impractical, inefficient, and time-consuming. Automation-based surveillance systems appeared to overcome these limitations. However, the automatic systems have some challenges such as occlusion and retaining images smoothly and continuously. This research proposes a weighted resampling particle filter approach for human tracking to handle these challenges. The primary functions of the proposed system are human detection, human monitoring, and camera control. We used the codebook matching algorithm to define the human region as a target and track it, and we used the practical filter algorithm to follow and extract the target information. Consequently, the obtained information was used to configure the camera control. The experiments were tested in various environments to prove the stability and performance of the proposed system based on the active camera.https://www.mdpi.com/2504-2289/4/4/27color distributionparticle filterhuman trackingcodebook matchingPID controllerGMM |
| spellingShingle | Liang Cheng Chang Shreya Pare Mahendra Singh Meena Deepak Jain Dong Lin Li Amit Saxena Mukesh Prasad Chin Teng Lin An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering Big Data and Cognitive Computing color distribution particle filter human tracking codebook matching PID controller GMM |
| title | An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering |
| title_full | An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering |
| title_fullStr | An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering |
| title_full_unstemmed | An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering |
| title_short | An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering |
| title_sort | intelligent automatic human detection and tracking system based on weighted resampling particle filtering |
| topic | color distribution particle filter human tracking codebook matching PID controller GMM |
| url | https://www.mdpi.com/2504-2289/4/4/27 |
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