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False Positive Eliminating Using Frame Association Information

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Published:15 March 2019Publication History

ABSTRACT

As a fundamental technology of human motion analysis, video based pose estimation has attracted more and more attention of researchers. While most mainstream methods treated videos as a collection of unrelated frames, random false positives caused by light and shadow changes will bring greater uncertainty to the results of human body estimation. To eliminate these false positives in multi-person 2D pose estimation, a method of multi-person 2D pose estimation using the time-space relationship of adjacent frames is proposed. At first, Frame Association Information(FAI) is defined to represent the relationship between person objects in adjacent frames, which contents similarity of position, size and poses. Then, a method of false positives eliminating is designed using FAIs between frames, which can identify and remove false positives in frames according to their similarities to human objects in a benchmark frame. The following experiments show the effectiveness of our method.

References

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    • Published in

      cover image ACM Other conferences
      ICIAI '19: Proceedings of the 2019 3rd International Conference on Innovation in Artificial Intelligence
      March 2019
      279 pages
      ISBN:9781450361286
      DOI:10.1145/3319921

      Copyright © 2019 ACM

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      Publication History

      • Published: 15 March 2019

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