A Correlation Filter Target Tracking Algorithm Based on Continuous Convolution Operator and Spatial-Temporal Regularization Term

• Format: Article
• Language: zho
• Published: The Northwestern Polytechnical University 2019-12-01
• Series: Xibei Gongye Daxue Xuebao
• Subjects: target tracking; correlation filter; continuous convolution operator; spatial-temporal regularization term
• Online Access: https://www.jnwpu.org/articles/jnwpu/full_html/2019/06/jnwpu2019376p1264/jnwpu2019376p1264.html

In order to accurately estimate the location of a target that is occluded and rotated rapidly by the STRCF algorithm, a correlation filter target tracking algorithm based on continuous convolution operator and spatial-temporal regularization term is proposed. The algorithm uses interpolation operators to transform a response function into a continuous function within a certain period, thus enhancing the accuracy of target location. Spatial-temporal regularization terms are added to the new model of correlation filter to ensure that it is similar to the model of the previous frame of image and that the algorithm is more robust. A fast multi-scale filter is used to update the scale, thus improving the computational efficiency. The experimental results show that the average overlap rate of the proposed algorithm can reach 73% and that the central position error is less than 8.2. The proposed algorithm can achieve a real-time and robust target tracking.