International Journal of Internet, Broadcasting and Communication

  • 제13권2호
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  • Pages.156-165
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  • 2021
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  • 2288-4920(pISSN)
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  • 2288-4939(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
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Object Tracking with Histogram weighted Centroid augmented Siamese Region Proposal Network

  • 투고 : 2021.03.17
  • 심사 : 2021.03.22
  • 발행 : 2021.05.31
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초록

In this paper, we propose an histogram weighted centroid based Siamese region proposal network for object tracking. The original Siamese region proposal network uses two identical artificial neural networks which take two different images as the inputs and decide whether the same object exist in both input images based on a similarity measure. However, as the Siamese network is pre-trained offline, it experiences many difficulties in the adaptation to various online environments. Therefore, in this paper we propose to incorporate the histogram weighted centroid feature into the Siamese network method to enhance the accuracy of the object tracking. The proposed method uses both the histogram information and the weighted centroid location of the top 10 color regions to decide which of the proposed region should become the next predicted object region.

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과제정보

This work was supported by the Technology development Program(S2840023)funded by the Ministry of SMEs and Startups(MSS, Korea).

참고문헌

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