【作者单位】1College of Computer Science and Technology, Taiyuan Normal University, Taiyuan, China
【年份】2022
【卷号】Vol.10
【页码】118512-118521
【关键词】Kalman filter multi-object tracking movement behavior multi-pedestrian tracking AFM
【摘要】 Most multi-object tracking methods have achieved good results in tracking multiple pedestrians with Kalman filter, but their tracking performance in crowded scenes is still poor due to pedestrian avoidance and frequent occlusion. In crowded scenes, t...
