Perceived Acceleration in Stereoscopic Animation

In stereoscopic media, a sensation of depth is produced through the differences of images presented to the left and the right eyes. These differences are a result of binocular parallax caused by the separation of the cameras used to capture the scene. Creators of stereoscopic media face the challenge of producing compelling depth while restricting the amount of parallax to a comfortable range. Control of camera separation is a key manipulation to control parallax. Sometimes, stereoscopic warping is used in post-production process to selectively increase or decrease depth in certain regions of the image. However, mismatches between camera geometry and natural stereoscopic geometry can theoretically produce nonlinear distortions of perceived space. The relative expansion or compression of the stereoscopic space, in theory, should affect the perceived acceleration of objects moving through that space. This thesis suggests that viewers are tolerant of effects of distortions when perceiving acceleration in a stereoscopic scene

Uncalibrated Relief Reconstruction and Model Alignment from Binocular Disparities

We propose a computational scheme for uncalibrated reconstruction of scene structure up to a relief transformation from binocular disparities. This scheme, which we call regional disparity correction (RDC), is motivated both by computational considerations and by psychophysical observations regarding human stereoscopic depth perception. We describe an implementation of RDC, and demonstrate its performance experimentally. As an example of applications of RDC, we show how it can be used to align a three-dimensional object model with an uncalibrated disparity field. Keywords: stereo, disparity, uncalibrated reconstruction, relief transformation, human vision, model alignment 1 Introduction Binocular disparities, i.e., the slightly different views captured by two eyes or cameras, can convey important information about the three-dimensional structure of the scene. In machine vision, the classical approach is to combine disparities with precise camera calibration information in order to r..