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Stereo Depth Mapping via Axis-Aligned Warping
Conference paper

Stereo Depth Mapping via Axis-Aligned Warping

Bing Li, Chia-Wen Lin, Cheng Zheng, Shan Liu and C.-C. Jay Kuo
Proceedings - International Conference on Image Processing, ICIP, Vol.2019-September, pp.4305-4309
09/2019

Abstract

Depth mapping image editing stereoscopic image warping Software Computer Vision and Pattern Recognition Signal Processing
Viewing various stereo images under different viewing conditions has escalated the need for efficient and effective depth mapping techniques for adjusting the depths and sizes of objects to match user preference. Existing methods mainly alter the depth of an object through non-uniform region warping, which, however, often cause severe depth or shape distortions, due to improper warping such as local rotations. In this paper, we propose a new object depth mapping scheme based on axis-aligned warping. The proposed axis-aligned-warping based optimization model can simultaneously adjust the depths and sizes of selected objects to their target values without introducing severe shape distortions. Experimental results demonstrate that our method achieves high flexibility and effectiveness in adjusting the size and depth of object compared with existing methods.

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