Improving Motion Estimation Using Image-Driven Functions and Hybrid Scheme

  • Duc Dung Nguyen
  • Jae Wook Jeon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7087)


We introduce an alternative method to improve optical flow estimation using image data for control functions. Base on the nature of object motion, we tune the energy minimization process with an image-adaptive scheme embedded inside the energy function. We propose a hybrid scheme to improve the quality of the flow field and we use it along with the multiscale approach to deal with large motion in the sequence. The proposed hybrid scheme take advantages from multigrid solver and the pyramid model. Our proposed method yields good estimation results and it shows the potential to improve the performance of a given model. It can be applied to other advanced models. By improving quality of motion estimation, various applications in intelligent systems are available such as gesture recognition, video analysis, motion segmentation, etc.


Optical Flow Motion Estimation Gesture Recognition Hybrid Scheme Angular Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Duc Dung Nguyen
    • 1
  • Jae Wook Jeon
    • 1
  1. 1.Department of Electrical and Computer EngineeringSungkyunkwan UniversityKorea

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