Combined block-matching and adaptive differential motion estimation in a hierarchical multi-scale framework

Matthias Brüggemann; Rüdiger Kays; Paul Springer; Oliver Erdler

doi:10.1117/12.2179165

4 March 2015 Combined block-matching and adaptive differential motion estimation in a hierarchical multi-scale framework

Matthias Brüggemann, Rüdiger Kays, Paul Springer, Oliver Erdler

Author Affiliations +

Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94430V (2015) https://doi.org/10.1117/12.2179165
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China

Abstract

In this paper we present a combination of block-matching and differential motion field estimation. We initialize the motion field using a predictive hierarchical block-matching approach. This vector field is refined by a pixel-recursive differential motion estimation method. We integrate image warping and adaptive filter kernels into the Horn and Schunck differential optical flow estimation approach to break the block structure of the initial correspondence vector fields and compute motion field updates to fulfill the smoothness constraint inside motion boundaries. The influence of occlusion areas is reduced by integrating an in-the-loop occlusion detection and adjusting the adaptive filter weights in the iteration process. We integrate the combined estimation into a hierarchical multi-scale framework. The refined motion on the current scale is upscaled and used as prediction for block-matching motion estimation on the next scale. With the proposed system we are able to combine the advantages of block-matching and differential motion estimation and achieve a dense vector field with floating point precision even for large motion.

Citation Download Citation

Matthias Brüggemann, Rüdiger Kays, Paul Springer, and Oliver Erdler "Combined block-matching and adaptive differential motion estimation in a hierarchical multi-scale framework", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94430V (4 March 2015); https://doi.org/10.1117/12.2179165

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