Paper Info
Title
Shift-Map based stereo image retargeting with disparity adjustment
Abstract
This paper introduces a novel image retargeting algorithm for 3D images given as pairs of stereo images. In the context of 3D image retargeting, the novel viewpoint advocated in this paper is that the geometric consistency in the form of preserving disparity values should not be an overpowering objective formulated as hard constraints. Instead, for maximizing viewing experience and comfort, it is desirable to simultaneously retarget the images as well as adjust the disparity values. The proposed retargeting algorithm is based on the methods of shift-map and importance filtering, and the main technical contribution of this paper is a successful extension of these earlier techniques to 3D images. We have evaluated the proposed method extensively, and the results demonstrate the efficiency of the proposed method as well as its potential for producing high-quality outputs. In particular, comparing with the state-of-the-art, the proposed method has a considerably shorter running time, and at the same time, it produces the retargeted 3D images that are more agreeable and pleasing for viewing.
Year
DOI
Venue
2012
10.1007/978-3-642-37447-0_35
ACCV (4)
Keywords
Field
DocType
proposed retargeting algorithm,novel image,stereo image,viewing experience,disparity adjustment,image retargeting,geometric consistency,earlier technique,disparity value,novel viewpoint
Computer vision,Pattern recognition,Computer science,Salient objects,Seam carving,Filter (signal processing),Retargeting,Geometric consistency,Artificial intelligence,Stereo image,3d image
Conference
Citations 
PageRank 
References 
4
0.41
15
Authors
2
Name
Order
Citations
PageRank
Shaoyu Qi190.80
Jeffrey Ho22190101.78