Depth Reconstruction Uncertainty Improvement for Skewed Parallel Stereo Pair Cameras Using Dithering Approach

Abstract: Each point in the space is defined by its three dimensions position (x,y,z). However, capturing this point with a camera only translates it to a two dimensional point (x,y). The reconstruction of the missing dimension z is needed to locate the point in the space. The skewed parallel cameras provide the mechanism for obtaining 3D information in a wide field of view. Due to discretization in the image planes, the 3D space is quantized by iso-disparity surfaces. In this thesis, a mathematical model relating the stereo setup parameters with the iso-disparities is developed and used for depth estimation. To reduce the uncertainty (quantization error) in the depth reconstruction, the dithering approach is proposed; therefore a dithering signal is estimated and generated to change the setup parameters. The simulation results show how the uncertainty of the depth reconstruction can be improved by this model.