Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Object Tracking using Feature Map from Convolutional Neural Network

컨볼루션 신경망의 특징맵을 사용한 객체 추적

  • Lim, Suchang (Dept. of Computer Science, Sunchon National University) ;
  • Kim, Do Yeon (Dept. of Computer Engineering, Sunchon National University)
  • Received : 2016.12.14
  • Accepted : 2017.01.13
  • Published : 2017.02.28
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Abstract

The conventional hand-crafted features used to track objects have limitations in object representation. Convolutional neural networks, which show good performance results in various areas of computer vision, are emerging as new ways to break through the limitations of feature extraction. CNN extracts the features of the image through layers of multiple layers, and learns the kernel used for feature extraction by itself. In this paper, we use the feature map extracted from the convolution layer of the convolution neural network to create an outline model of the object and use it for tracking. We propose a method to adaptively update the outline model to cope with various environment change factors affecting the tracking performance. The proposed algorithm evaluated the validity test based on the 11 environmental change attributes of the CVPR2013 tracking benchmark and showed excellent results in six attributes.

Keywords

References

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