Aerial Multi-target Detection Based on Spatial-Temporal Information and Trajectory Association

To tackle the problem that the targets in the image have few pixels and the targets are adjacent to each other and occluded each other, an aerial multi-target detection algorithm is proposed based on spatial-temporal information and trajectory association. Firstly, the pixel-based background modeling algorithm is used to obtain the target space information, and the neighboring frame difference algorithm is used to obtain the target time information. The time and space information are combined to get a spatial-temporal information map. Secondly, the Kalman predictor is used to predict the target position, and the Hungarian matching algorithm is used to correlate the target to obtain the target trajectory. Based on the target trajectory, the missed detection targets are supplemented to improve the target recall rate. Finally, based on the target trajectory features which are extracted in segments, the false alarm targets are filtered out to improve the target precision rate. Experimental videos with aerial multi-target are adopted for experimental verification, and the experimental results show that the proposed algorithm has good detection performance, with the recall rate higher than 96%, the precision rate higher than 98%, and the F-measure higher than 97%.