特征点辅助的时空上下文目标跟踪与定位

针对动态目标跟踪中快速运动和目标遮挡而跟踪失败问题,提出了一种特征点辅助的时空上下文跟踪算法。首先提取目标特征点,通过特征点匹配和光流跟踪方法进行目标追踪,获得目标预估位置;其次,建立特征点变化率和时空上下文模型更新率关系模型,实时调控更新率,防止引入错误信息;最后,在预估位置区域内,构建局部上下文外观模型,计算与时空上下文模型的相关性获取置信图,进一步精确定位目标。算法在一组测试视频集中进行验证,相比目前4种主流算法(平均跟踪成功率最高为60%,平均跟踪误差最小为26.14 pixel),本算法综合性能达到最优,平均跟踪成功率为90%,平均跟踪误差为7.47 pixel,平均跟踪速率25.31 f/s。在双目视觉移动机器人平台上对随机运动目标进行跟踪实验,在背景干扰、遮挡、目标旋转和快速运动等组合情况下,跟踪成功率97.4%,跟踪距离平均相对误差为4.05%。

Object tracking and location with spatio temporal context assisted by key points

Aimed at the problems of dynamic target tracking failure in the situation of fast motion and target occlusion, a spatio temporal context tracking algorithm is proposed based on key points. Firstly, the key points of the target are extracted, and the predicted location of the object is obtained by combining key points matching with optical flow tracking. Then, the relationship model between key points change rate and spatio temporal context model updating rate is established to control the update rate in real time. In this way, the introduction of erroneous information can be prevented. Finally, a local context appearance model is constructed in the predicted location region, and the correlation between the spatio temporal context model and the local context appearance model is computed to obtain the confidence map. Furthermore, the target is located accurately. The algorithm is validated in the test video, the highest average tracking success rate is 60% and the minimum average center error is 26.14 pixel. Compared to the 4 types of current major algorithms, the comprehensive performance of the proposed algorithm is superior to other methods, whose average tracking success rate is 90%, average center point error is 7.47 pixel and the average tracking rate is 25.31 frames per second. In the case of background interference, occlusion, target rotation and rapid motion, the mobile robot with binocular vision is used to track the random moving target. The success rate is 97.4%, and the average relative error of tracking distance is 4.05%.