Adaptive Search-based Hierarchical Motion Estimation using Spatial Priors

نویسندگان

  • Michael Santoro
  • Ghassan Al-Regib
  • Yücel Altunbasak
چکیده

Since motion estimation via block matching is an ill-posed problem, it requires the use of smoothness constraints to regularize the motion field. The block matching error and smoothness constraints together form an energy expression to be minimized. Motion vectors (MVs) from a candidate set are used to determine which MV minimizes the overall energy. These MVs, which may consist of spatial or temporal MVs, determine the quality of the motion field. Therefore, to ensure a high-quality motion field, we propose a new method to improve the quality of the MVs. The proposed method uses a novel approach to incorporate prior spatial MVs into block matching. By incorporating these MVs into block matching, we significantly reduce the size of the candidate set and improve the quality of the motion field.

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تاریخ انتشار 2012