Abstract
Color feature is mainly adopted in the traditional particle filter method when tracking the target. In view of the problem of failing to track the target caused by background similarity and occlusion, an improved particle filter tracking algorithm based on color histogram and convolution network is proposed, which makes full use of the color feature and convolution feature of the target. Experiments show that compared with the traditional tracking algorithm based on particle filter, the proposed algorithm has a good ability to adapt to changes in the environment around the target.
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Gao, S., Zhou, L., Xie, Q. (2018). An Improved Particle Filter Target Tracking Algorithm Based on Color Histogram and Convolutional Network. In: Geng, X., Kang, BH. (eds) PRICAI 2018: Trends in Artificial Intelligence. PRICAI 2018. Lecture Notes in Computer Science(), vol 11013. Springer, Cham. https://doi.org/10.1007/978-3-319-97310-4_17
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DOI: https://doi.org/10.1007/978-3-319-97310-4_17
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