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Ph.D. Student  

Publication Details

M. Grundmann, V. Kwatra, M. Han, I. Essa
Discontinuous Seam-Carving for Video Retargeting
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, USA, June 2010

We introduce a new algorithm for video retargeting that uses discontinuous seam-carving in both space and time for resizing videos. Our algorithm relies on a novel appearance-based temporal coherence formulation that allows for frame-by-frame processing and results in temporally discontinuous seams, as opposed to geometrically smooth and continuous seams. This formulation optimizes the difference in appearance of the resultant retargeted frame to the optimal temporally coherent one, and allows for carving around fast moving salient regions. 
Additionally, we generalize the idea of appearance-based coherence to the spatial domain by introducing piece-wise spatial seams. Our spatial coherence measure minimizes the change in gradients during retargeting, which preserves spatial detail better than minimization of color difference alone. We also show that per-frame saliency (gradient- based or feature-based) does not always produce desirable retargeting results and propose a novel automatically computed measure of spatio-temporal saliency. As needed, a user may also augment the saliency by interactive region-brushing. Our retargeting algorithm processes the video sequentially, making it conducive for streaming applications.

Bibtex entry

author = {M. Grundmann and V. Kwatra and M. Han and I. Essa },
title = {Discontinuous Seam-Carving for Video Retargeting},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2010},