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Tracking algorithm for non-rigid objects based on the shape prediction

Research Project

Project/Area Number 26330217
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Perceptual information processing
Research InstitutionNational Institute of Advanced Industrial Science and Technology

Principal Investigator

Nishida Kenji  国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 主任研究員 (50344148)

Project Period (FY) 2014-04-01 – 2018-03-31
Project Status Completed (Fiscal Year 2017)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Keywordsオブジェクト・トラッキング / コンピュータ・ビジョン / パターン認識 / 画像処理 / スポーツ工学 / 姿勢推定
Outline of Final Research Achievements

A novel algorithm for tracking by shape with deforming prediction is proposed. The algorithm is based on the similarity of the predicted and actual object shape. Second order approximation for feature point movement by Taylor expansion is adopted for shape prediction, and the similarity is measured by using chamfer matching of the predicted and the actual shape. Chamfer matching is also used to detect the feature point movements to predict the object deformation. The proposed algorithm is applied to the tracking of a skier and showed a good tracking and shape prediction performance.

Report

(5 results)
  • 2017 Annual Research Report   Final Research Report ( PDF )
  • 2016 Research-status Report
  • 2015 Research-status Report
  • 2014 Research-status Report
  • Research Products

    (5 results)

All 2016 2015

All Journal Article (4 results) (of which Peer Reviewed: 4 results,  Open Access: 2 results,  Acknowledgement Compliant: 2 results) Presentation (1 results)

  • [Journal Article] Preindication Mining for Predicting Pedestrian.Action Change2016

    • Author(s)
      K.Nishida, T.Kobayashi, T.Iwamoto. S.Yamasaki
    • Journal Title

      Computational Intelligence

      Volume: 669 Pages: 359-370

    • DOI

      10.1007/978-3-319-48506-5_18

    • ISBN
      9783319485041, 9783319485065
    • Related Report
      2016 Research-status Report
    • Peer Reviewed / Open Access
  • [Journal Article] Accuracy Evaluation of Second-Order Shape Prediction on Tracking Non-Rigid Objects2015

    • Author(s)
      Kenji Nishida, Takumi Kobayashi, Jun Fujiki
    • Journal Title

      International Journal on Advances in Systems and Measurements

      Volume: 8 Pages: 201-209

    • Related Report
      2015 Research-status Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Video image recovery for occluded sklier's form by combining forward and backward prediction using motion feature2015

    • Author(s)
      Kenji Nishida, Takumi Kobayashi, Jun Fujiki
    • Journal Title

      Science and Skiing

      Volume: 6 Pages: 251-259

    • Related Report
      2014 Research-status Report
    • Peer Reviewed
  • [Journal Article] The Effect of 2nd-Order Shape Prediction on Tracking Non-Rigid Objects2015

    • Author(s)
      Kenji Nishida, Takumi Kobayashi, Jun Fujiki
    • Journal Title

      Proc. 7th International Conference on Pervasive Patterns and Applications

      Volume: 1 Pages: 60-63

    • Related Report
      2014 Research-status Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Presentation] The Effect of 2nd-Order Shape Prediction on Tracking Non-Rigid Objects2015

    • Author(s)
      Kenji Nishida, Takumi Kobayashi, Jun Fujiki
    • Organizer
      7th International Conference on Pervasive patterns and Applications
    • Place of Presentation
      ニース、フランス
    • Year and Date
      2015-03-22 – 2015-03-27
    • Related Report
      2014 Research-status Report

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Published: 2014-04-04   Modified: 2019-03-29  

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