Theory and Method of Data Collection for Mixed Traffic Flow Based on Image Processing Technology
| Autor: | En-Chen Liu, Xifan Yao, Zhi-Bin Xu, Dong-yuan Ge, Wen-Jiang Xiang |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Data collection
Article Subject Computer science business.industry General Mathematics General Engineering Cognitive neuroscience of visual object recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications Image processing 02 engineering and technology Kalman filter Engineering (General). Civil engineering (General) Object (computer science) Traffic flow Video tracking QA1-939 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence TA1-2040 business Intelligent transportation system Mathematics |
| Zdroj: | Mathematical Problems in Engineering, Vol 2021 (2021) |
| ISSN: | 1024-123X |
| DOI: | 10.1155/2021/9966494 |
| Popis: | As a key element of ITS (intelligent traffic systems), traffic information collection facilities play a key role, with ITS being able to analyze the state of mixed traffic more appropriately and can provide effective technical support for the design, management, and the evaluation of constructions. Traffic Infrastructure. Focusing on image processing technology, this study takes pedestrians, electric motor, and vehicles in mixed traffic flow as the research object, and Gaussian mixed model, Kalman filtering, and Fisher linear discriminant are introduced in the recognition system. On this basis, the mixed motion flow data acquisition framework model is elaborated in detail, which includes attribute extraction, object recognition, and object tracking. Given the difficulty in capturing reliable images of objects in real traffic scenes, this study adopted a novel background and foreground classification method with region proposal network so as to decrease the number of regions proposal from 2000 to 300, which can detect objects fast and accurately. Experiments demonstrate that the designed programme can collect the flow data by detecting and tracking moving object in the surveillance video for mixed traffic. Further integration of various modules to achieve integrated collection is another important task for further research and development. In the future, research on dynamic calibration of monocular vision will be carried out for distance measurement and speed measurement of vehicles and pedestrians. |
| Databáze: | OpenAIRE |
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