Accuracy improvement of depth estimation with tilted optics by optimizing neural network

We have been investigating a novel depth estimation system that adopts tilted-lens optics for real-time usage, e.g., automotive tasks. Herein, we obtained depth values for each pixel from the sharpness ratio of only two tilted optics images; we used a monocular camera system with a spectroscopic mirror. However, the method causes some estimation errors because of the difference between the optical theory and the actual camera system. Therefore, to reduce the error, we adopted a neural network to obtain the depth map. In this paper, we report our improvement by optimizing the neural network construction which calculates the depth value for each pixel from 3 x 3 pixel values at each image and y-coordinate.