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http://dx.doi.org/10.9717/kmms.2021.24.6.796

Object Tracking Algorithm using Feature Map based on Siamese Network  

Lim, Su-Chang (Dept. of Computer Engineering, Sunchon National University)
Park, Sung-Wook (Dept. of Computer Engineering, Sunchon National University)
Kim, Jong-Chan (Dept. of Computer Engineering, Sunchon National University)
Ryu, Chang-Su (Dept. of Cartoon & Game Motion Graphic, Yewon Arts University)
Publication Information
Journal of Korea Multimedia Society / v.24, no.6, 2021 , pp. 796-804 More about this Journal
Abstract
In computer vision, visual tracking method addresses the problem of localizing an specific object in video sequence according to the bounding box. In this paper, we propose a tracking method by introducing the feature correlation comparison into the siamese network to increase its matching identification. We propose a way to compute location of object to improve matching performance by a correlation operation, which locates parts for solving the searching problem. The higher layer in the network can extract a lot of object information. The lower layer has many location information. To reduce error rate of the object center point, we built a siamese network that extracts the distribution and location information of target objects. As a result of the experiment, the average center error rate was less than 25%.
Keywords
Computer Vision; Convolutional Neural Networks; Deep Learning; Object Tracking; Siamese Network;
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