Louvain-Based Traffic Object Detection for Roadside 4D Millimeter-Wave Radar

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dc.creatorGong, Bowen
dc.creatorSun, Jinghang
dc.creatorLin, Ciyun
dc.creatorLiu, Hongchao
dc.creatorSun, Ganghao
dc.date.accessioned2024-03-18T18:46:17Z
dc.date.available2024-03-18T18:46:17Z
dc.date.issued2024
dc.description© 2024 by the authors. cc-by
dc.description.abstractObject detection is the fundamental task of vision-based sensors in environmental perception and sensing. To leverage the full potential of roadside 4D MMW radars, an innovative traffic detection method is proposed based on their distinctive data characteristics. First, velocity-based filtering and region of interest (ROI) extraction were employed to filter and associate point data by merging the point cloud frames to enhance the point relationship. Then, the Louvain algorithm was used to divide the graph into modularity by converting the point cloud data into graph structure and amplifying the differences with the Gaussian kernel function. Finally, a detection augmentation method is introduced to address the problems of over-clustering and under-clustering based on the object ID characteristics of 4D MMW radar data. The experimental results showed that the proposed method obtained the highest average precision and F1 score: 98.15% and 98.58%, respectively. In addition, the proposed method showcased the lowest over-clustering and under-clustering errors in various traffic scenarios compared with the other detection methods.
dc.identifier.citationGong, B., Sun, J., Lin, C., Liu, H., & Sun, G.. 2024. Louvain-Based Traffic Object Detection for Roadside 4D Millimeter-Wave Radar. Remote Sensing, 16(2). https://doi.org/10.3390/rs16020366
dc.identifier.urihttps://doi.org/10.3390/rs16020366
dc.identifier.urihttps://hdl.handle.net/2346/97764
dc.language.isoeng
dc.subjectLouvain
dc.subjectpoint cloud data processing
dc.subjectroadside 4D millimeter-wave radar
dc.subjecttraffic object detection
dc.titleLouvain-Based Traffic Object Detection for Roadside 4D Millimeter-Wave Radar
dc.typeArticle

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