Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion
The intelligent transportation system (ITS) is inseparable from people’s lives, and the development of artificial intelligence has made intelligent video surveillance systems more widely used. In practical traffic scenarios, the detection and tracking of vehicle targets is an important core aspect o...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/12/4562 |
| _version_ | 1827656614854787072 |
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| author | Dongpo Xu Yunqing Liu Qian Wang Liang Wang Renjun Liu |
| author_facet | Dongpo Xu Yunqing Liu Qian Wang Liang Wang Renjun Liu |
| author_sort | Dongpo Xu |
| collection | DOAJ |
| description | The intelligent transportation system (ITS) is inseparable from people’s lives, and the development of artificial intelligence has made intelligent video surveillance systems more widely used. In practical traffic scenarios, the detection and tracking of vehicle targets is an important core aspect of intelligent surveillance systems and has become a hot topic of research today. However, in practical applications, there is a wide variety of targets and often interference factors such as occlusion, while a single sensor is unable to collect a wealth of information. In this paper, we propose an improved data matching method to fuse the video information obtained from the camera with the millimetre-wave radar information for the alignment and correlation of multi-target data in the spatial dimension, in order to address the problem of poor recognition alignment caused by mutual occlusion between vehicles and external environmental disturbances in intelligent transportation systems. The spatio-temporal alignment of the two sensors is first performed to determine the conversion relationship between the radar and pixel coordinate systems, and the calibration on the timeline is performed by Lagrangian interpolation. An improved Hausdorff distance matching algorithm is proposed for the data dimension to calculate the similarity between the data collected by the two sensors, to determine whether they are state descriptions of the same target, and to match the data with high similarity to delineate the region of interest (ROI) for target vehicle detection. |
| first_indexed | 2024-03-09T22:31:51Z |
| format | Article |
| id | doaj.art-60dbaee1d9a54ce793efc5b1c24385e6 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T22:31:51Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-60dbaee1d9a54ce793efc5b1c24385e62023-11-23T18:55:22ZengMDPI AGSensors1424-82202022-06-012212456210.3390/s22124562Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video FusionDongpo Xu0Yunqing Liu1Qian Wang2Liang Wang3Renjun Liu4School of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaSchool of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaSchool of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaIntelligent Perception and Processing Technology Laboratory, Beijing 100124, ChinaSchool of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaThe intelligent transportation system (ITS) is inseparable from people’s lives, and the development of artificial intelligence has made intelligent video surveillance systems more widely used. In practical traffic scenarios, the detection and tracking of vehicle targets is an important core aspect of intelligent surveillance systems and has become a hot topic of research today. However, in practical applications, there is a wide variety of targets and often interference factors such as occlusion, while a single sensor is unable to collect a wealth of information. In this paper, we propose an improved data matching method to fuse the video information obtained from the camera with the millimetre-wave radar information for the alignment and correlation of multi-target data in the spatial dimension, in order to address the problem of poor recognition alignment caused by mutual occlusion between vehicles and external environmental disturbances in intelligent transportation systems. The spatio-temporal alignment of the two sensors is first performed to determine the conversion relationship between the radar and pixel coordinate systems, and the calibration on the timeline is performed by Lagrangian interpolation. An improved Hausdorff distance matching algorithm is proposed for the data dimension to calculate the similarity between the data collected by the two sensors, to determine whether they are state descriptions of the same target, and to match the data with high similarity to delineate the region of interest (ROI) for target vehicle detection.https://www.mdpi.com/1424-8220/22/12/4562intelligent transportation systemsmillimeter-wave radarvideospatio-temporal alignmenttarget matching |
| spellingShingle | Dongpo Xu Yunqing Liu Qian Wang Liang Wang Renjun Liu Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion Sensors intelligent transportation systems millimeter-wave radar video spatio-temporal alignment target matching |
| title | Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion |
| title_full | Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion |
| title_fullStr | Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion |
| title_full_unstemmed | Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion |
| title_short | Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion |
| title_sort | target detection based on improved hausdorff distance matching algorithm for millimeter wave radar and video fusion |
| topic | intelligent transportation systems millimeter-wave radar video spatio-temporal alignment target matching |
| url | https://www.mdpi.com/1424-8220/22/12/4562 |
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