DocumentCode :
3408893
Title :
Hybrid shift map for video retargeting
Author :
Hu, Yiqun ; Rajan, Deepu
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2010
fDate :
13-18 June 2010
Firstpage :
577
Lastpage :
584
Abstract :
We propose a new method for video retargeting, which can generate spatial-temporal consistent video. The new measure called spatial-temporal naturality preserves the motion in the source video without any motion analysis in contrast to other methods that need motion estimation. This advantage prevents the retargeted video from degenerating due to the propagation of the errors in motion analysis. It allows the proposed method to be applied on challenging videos with complex camera and object motion. To improve the efficiency of the retargeting process, we retarget video using a 3D shift map in low resolution and refine it using an incremental 2D shift map in higher resolution. This new hierarchical framework, denoted as hybrid shift map, can produce satisfactory retargeting results while significantly improving the computational efficiency.
Keywords :
motion estimation; object recognition; video signal processing; 3D shift map; hybrid shift map; motion analysis; motion estimation; object motion; spatial-temporal consistent video; video retargeting; Cameras; Computational efficiency; Energy measurement; Energy resolution; Hybrid power systems; Motion analysis; Motion estimation; Motion measurement; Pixel; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
Conference_Location :
San Francisco, CA
ISSN :
1063-6919
Print_ISBN :
978-1-4244-6984-0
Type :
conf
DOI :
10.1109/CVPR.2010.5540162
Filename :
5540162
Link To Document :
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