A method of producing depth maps for depth-image-based rendering (DIBR) of stereoscopic views is proposed and tested. The method is based on depth-from-defocus techniques, utilizing two original images, one with the camera focused at a near point and the other with it focused at a far point in the captured scene to produce depth maps from blur at edge locations. It is assumed that the level of blur at an edge reflects the distance it is from the focused distance. For each image, estimates of the level of blur edges at local regions are obtained by determining the optimal scale for edge
detection based on a luminance gradient. An Edge-Depth map is then obtained by evaluating differences in blur for corresponding regions in the two images. This is followed by an additional process in which regions in the Edge-Depth map that have no depth values are filled to produce a Filled-Depth map. A group of viewers assessed the depth quality of a representative set of stereoscopic images that were produced by DIBR using the two types of depth maps. It was
found that the stereoscopic images generated with the Filled-Depth and the Edge-Depth maps produced depth quality ratings that were higher than those produced by their monoscopic, two-dimensional counterparts. Images rendered using the Filled-Depth maps, but not the Edge-Depth maps, produced ratings of depth quality that were equal to those produced with factual, full depth maps. A hypothesis as to how the proposed method might be improved is discussed.
We propose a software-based minimum-time vergence control scheme
(MTVCS) for a parallel-axis stereoscopic camera (PASC). First, a
global horizontal disparity is estimated by using modified
binocular energy models and transformed stereoscopic images via
Radon Transform with a specified angle parameter. Second, with the
estimated global disparity, the actual disparity command is
derived through a nonlinear function such that the resulting
horizontal disparity is equal to the command exactly with the
control in a fastest time interval. Through experimental results,
we will show that the proposed MTVCS achieves better tracking and
regulating performances than those of the previous scheme.