This paper addresses the problem of remapping the disparity range
of stereoscopic images and video. Such operations are highly important
for a variety of issues arising from the production, live
broadcast, and consumption of 3D content. Our work is motivated
by the observation that the displayed depth and the resulting 3D
viewing experience are dictated by a complex combination of perceptual,
technological, and artistic constraints. We first discuss the
most important perceptual aspects of stereo vision and their implications
for stereoscopic content creation. We then formalize these
insights into a set of basic disparity mapping operators. These operators
enable us to control and retarget the depth of a stereoscopic
scene in a nonlinear and locally adaptive fashion. To implement our
operators, we propose a new strategy based on stereoscopic warping
of the input video streams. From a sparse set of stereo correspondences,
our algorithm computes disparity and image-based
saliency estimates, and uses them to compute a deformation of the
input views so as to meet the target disparities. Our approach represents
a practical solution for actual stereo production and display
that does not require camera calibration, accurate dense depth maps,
occlusion handling, or inpainting. We demonstrate the performance
and versatility of our method using examples from live action postproduction,
3D display size adaptation, and live broadcast. An additional
user study and ground truth comparison further provide evidence
for the quality and practical relevance of the presented work.