RESUMO
Multiview displays, which are capable of displaying different view-images for viewers at different positions, can suffer from undesirable view-image mixing, called crosstalk. In this paper, we propose a method to minimize a class of crosstalk that occurs due to misalignment of flat panel displays and parallax barriers that constitute multiview displays. More specifically, our method is aimed at cases where flat panel displays and parallax barriers are non-parallel. First, we introduce our framework, which associates homography matrices to sets of pixels visible through parallax barriers. Then, we propose an iterative method for finding pixels that are visible for a view-point. By using a stripe test pattern, the homography matrix that corresponds to a set of visible pixels can be found by monitoring the deformation of the stripe test pattern. Last, we experimentally check the validity of the iterative method and demonstrate that the proposed method successfully corrects the geometric distortion of a 3D image.
RESUMO
In this paper, we propose a multiview 3D display calibration algorithm that compensates for misalignment between constituent layers. To minimize distortion of the 3D image due to misalignment, we employ an iterative algorithm using camera feedback. We first establish a mathematical model for the multiview display and predict distortion of a test image pattern due to misalignment. Then, we define two characteristic features of the feedback camera image that indicate the status of the alignment. Based on the mathematical model, we design a compensation algorithm that consists of cascaded one-dimensional root-finding blocks for two-dimensional optimization. Finally, we experimentally verify the image distortion model, convergence of the iterative algorithm, and image quality improvement. The accuracy of the proposed algorithm exceeds the required accuracy for linear extrinsic crosstalk compensation.
