Search Region Prediction for Motion Estimation Based on Neural Network Vector Quantization

  • DaeHyun Ryu
  • HyungJun Kim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


We present a new search region prediction method using frequency sensitive competitive learning vector quantization for motion estimation of image sequences. The proposed method can decrease the computation time because of the smaller number of search points compared to other methods, and also reduces the bits required to represent motion vectors. The results of experiments show that the proposed method provides competitive PSNR values compared to other block matching algorithms while reducing the number of search points and minimizing the complexity of the search region prediction process.


Motion Vector Motion Estimation Vector Quantization Search Point Full Search 
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 2006

Authors and Affiliations

  • DaeHyun Ryu
    • 1
  • HyungJun Kim
    • 1
  1. 1.Division of Information TechnologyHansei UniversityKorea

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