Local temporal coherence for object-aware keypoint selection in video sequences

Songlin Du*, Takeshi Ikenaga

*Corresponding author for this work

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


Local feature extraction is an important solution for video analysis. The common framework of local feature extraction consists of a local keypoint detector and a keypoint descriptor. Existing keypoint detectors mainly focus on the spatial relationships among pixels, resulting in a large amount of redundant keypoints on background which are often temporally stationary. This paper proposes an object-aware local keypoint selection approach to keep the active keypoints on object and to reduce the redundant keypoints on background by exploring the temporal coherence among successive frames in video. The proposed approach is made up of three local temporal coherence criteria: (1) local temporal intensity coherence; (2) local temporal motion coherence; (3) local temporal orientation coherence. Experimental results on two publicly available datasets show that the proposed approach reduces more than 60% keypoints, which are redundant, and doubles the precision of keypoints.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers
EditorsBing Zeng, Hongliang Li, Qingming Huang, Abdulmotaleb El Saddik, Shuqiang Jiang, Xiaopeng Fan
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783319773827
Publication statusPublished - 2018
Event18th Pacific-Rim Conference on Multimedia, PCM 2017 - Harbin, China
Duration: 2017 Sept 282017 Sept 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10736 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other18th Pacific-Rim Conference on Multimedia, PCM 2017


  • Local feature extraction
  • Object-aware keypoint selection
  • Spatio-temporal keypoint
  • Video analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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