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Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 16 Similar Profiles
Motion estimation Engineering & Materials Science
Hardware Engineering & Materials Science
Image coding Engineering & Materials Science
Pixels Engineering & Materials Science
Motion Estimation Mathematics
High definition television Engineering & Materials Science
Data storage equipment Engineering & Materials Science
Processing Engineering & Materials Science

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Research Output 1990 2018

  • 1439 Citations
  • 18 h-Index
  • 192 Conference contribution
  • 89 Article

3D global trajectory and multi-view local motion combined player action recognition in volleyball analysis

Liu, Y., Huang, S., Cheng, X. & Ikenaga, T., 2018 Jan 1, Advances in Multimedia Information Processing – PCM 2018 - 19th Pacific-Rim Conference on Multimedia, 2018, Proceedings. Ngo, C-W., Yamasaki, T., Hong, R., Wang, M. & Cheng, W-H. (eds.). Springer-Verlag, p. 134-144 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11166 LNCS).

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

Action Recognition
Trajectories
Trajectory
Motion
Brick buildings

3D space motion dense based team tactical status detection in volleyball game analysis

Cheng, X. & Ikenaga, T., 2018 Feb 25, 2018 2nd International Conference on Digital Signal Processing, ICDSP 2018. Association for Computing Machinery, p. 32-36 5 p.

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

Trajectories
Trust Model
Anchors
Image matching
Computer vision
Image Matching

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

Du, S. & Ikenaga, T., 2018 Jan 1, Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers. Springer-Verlag, p. 539-549 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10736 LNCS).

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

Local Features
Feature extraction
Feature Extraction
Detectors
Detector