融合时空上下文的复杂背景下多运动目标检测

针对目标进、出视场和被部分遮挡情况下检测率低的问题，提出一种联合时空上下文的多运动目标检测算法STC-MMTD。首先，利用时间上下文信息，基于前后向运动历史图提取候选目标区域；然后，利用空间上下文信息和目标表观信息，通过基于稀疏编码的CRF模型计算目标置信度图；最后，计算候选目标区域的目标置信度，检测出多运动目标。实验结果表明，所提算法具有良好的检测性能，在保证较高定位精度的同时，查全率、查准率和F测度均高于其他多目标检测算法的。

Multiple moving targets detection under complex background by integrating spatio-temporal context#br# #br# #br#

In order to solve the problem of low detection rate when targets enter/leave the field of view, or targets are partially occluded, a multi moving targets detection algorithm based on spatio-temporal context is proposed. Firstly, the time context information is used to extract the candidate target region, which is based on the forward and backward motion history map. Secondly, the spatial context information and the target apparent information are used to calculate the target confidence map, which is based on the sparsely encoded CRF model. Finally, the target confidence of the candidate target region is calculated to detect the multiple moving targets. The experimental results show that the proposed algorithm has good detection performance, and it has higher recall rate, precision and F measure than other multi-target detection algorithms under the condition of guaranteeing high positioning accuracy.