stereoscopic 3D video, retargeting, disparity manipulation, image warping
Abstract We propose a disparity-constrained retargeting method for stereoscopic 3D video, which simultaneously resizes a binocular video to a new aspect ratio and remaps the depth to the perceptual comfort zone. First, we model distortion energies to prevent important video contents from deforming. Then, to maintain depth mapping stability, we model disparity variation energies to constraint the disparity range both in spatial and temporal domains. The last component of our method is a non-uniform, pixel-wise warp to the target resolution based on these energy models. Using this method, we can process the original stereoscopic video to generate new, high-perceptual-quality versions at different display resolutions. For evaluation, we conduct a user study; we also discuss the performance of our method.
Tsinghua University Press
Yi Liu, Lifeng Sun, Shiqiang Yang. A retargeting method for stereoscopic 3D video. Computational Visual Media 2015, 1(2): 119-127.