Dense flow field algorithm using binary descriptor and modified energy function

Dong Sung Pae, Hyeon Chan Oh, Sang Kyoo Park, Tae Koo Kang, Myo Taeg Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we describe a Dense Flow-Field algorithm for moving detection of an object using a binary descriptor and a modified energy function. Among the moving detection algorithms, a Dense SIFT-Flow algorithm is recently introduced. In the conventional Dense SIFT-Flow, a SIFT descriptor and an energy function are employed to make the flow vectors containing the movement information of each pixel at entire image. The matching process in the conventional SIFT-Flow algorithm uses descriptor information and a message-passing method in a coarse-to-fine scheme. Although the matching performance of the Dense SIFT-Flow is good for detecting the movement of each pixel, large computational time is needed. To reduce the complexity of the description part, the proposed method employs a binary descriptor. The process of the binary descriptor is simple enough to reduce the complexity. In addition, the energy function in the conventional Dense Flow-Field must be modified for the binary descriptor as replacing the unfair displacement term of the conventional energy function with a fair displacement term. From the experimental results, we can know that the proposed method is faster than the conventional method with respect to making flow field and more robust with respect to diagonal movements.

Original languageEnglish
Title of host publicationSII 2017 - 2017 IEEE/SICE International Symposium on System Integration
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1016-1021
Number of pages6
ISBN (Electronic)9781538622636
DOIs
Publication statusPublished - 2017 Jul 2
Event2017 IEEE/SICE International Symposium on System Integration, SII 2017 - Taipei, Taiwan, Province of China
Duration: 2017 Dec 112017 Dec 14

Publication series

NameSII 2017 - 2017 IEEE/SICE International Symposium on System Integration
Volume2018-January

Other

Other2017 IEEE/SICE International Symposium on System Integration, SII 2017
Country/TerritoryTaiwan, Province of China
CityTaipei
Period17/12/1117/12/14

Bibliographical note

Funding Information:
This work was supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education under Grant NRF-2016R1D1A1B01016071; by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education under Grant NRF-2016R1D1A1B03936281.

Funding Information:
*This work was supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education under Grant NRF-2016R1D1A1B01016071; by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education under Grant NRF-2016R1D1A1B03936281.

Publisher Copyright:
© 2017 IEEE.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Optimization
  • Engineering (miscellaneous)
  • Instrumentation
  • Computer Science Applications
  • Materials Science (miscellaneous)
  • Modelling and Simulation

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