融合运动信息和跟踪评价的高效卷积算子

针对基于方向梯度直方图与颜色命名的高效卷积算子(ECO-HC)算法缺少跟踪质量评价和滤波模板更新监督机制的问题，提出融合运动信息和跟踪评价的高效卷积算子. 将卡尔曼滤波器加入ECO-HC跟踪定位框架对目标执行联合跟踪，设计高置信度判别指标评价ECO-HC对每帧图像的跟踪效果，使用原始跟踪结果和卡尔曼滤波预测值的加权融合值，修正不满足判别指标的跟踪结果. 在滤波模板隔帧更新策略的基础上，加入当前帧跟踪结果质量评价信息，当2个条件同时满足时执行模板更新. 依托公开数据集OTB-2015评估算法性能，结果显示改进算法整体跟踪精确度、成功率和跟踪速率均优于原算法，在运动模糊、低分辨率、离开视野场景中的精确度分别提高3.0%、3.5%和2.8%，成功率分别提高3.8%、2.1%和4.0%. 改进算法在保证实时性的同时，有效提升了复杂场景下的跟踪效果.

Efficient convolution operators integrating motion information and tracking evaluation

An efficient convolution operator integrating motion information and tracking evaluation was proposed, to solve the problems that an efficient convolution operators algorithm named by histogram of oriented gridients and color (ECO-HC) lacks the quality evaluation of tracking result and the supervision mechanism of filter model updating. Firstly, the Kalman filter was added to the ECO-HC positioning framework to carry out joint tracking of objects. A high-confidence discriminant indicator was designed to evaluate the tracking result of ECO-HC for each frame of video. If the current frame tracking results did not meet the confidence requirement, the weighted fusion value of the algorithm tracking results and the predicted value of Kalman filter would be used as the final target tracking results. Then, based on the filter template update strategy of the original algorithm, the quality evaluation information of the current frame tracking results was added.The filter template update was performed when the two conditions were true. Finally, the performance of the improved algorithm was evaluated on a open data set OTB-2015. The results showed that the overall tracking precision, success rate and tracking rate of the algorithm with proposed operator were superior to the original algorithm. The precision in the scene with motion blur, low resolution and out of view was increased by 3.0%, 3.5% and 2.8% respectively, and the success rate was increased by 3.8%, 2.1% and 4.0% respectively. The proposed algorithm not only ensured the real-time performance, but also improved the tracking performance in complex scenes.