A 3-D Display Pipeline from Coded-Aperture Camera to Tensor Light-Field Display Through CNN


We propose an efficient pipeline from input to output for a tensor light-field display. Conventionally, a dense light field (i.e., tens of images taken with narrow viewpoint intervals) is required as an input in such displays. However, obtaining dense light fields is a challenging task for real scenes. To make the acquisition process more efficient, we adopted a coded-aperture camera as an input device, which is suitable for acquiring dense light fields in a compressive manner. Moreover, we modeled the entire process from acquisition to display using a convolutional neural network. As a result of training the network on a massive light field data, we can reproduce the whole light field on the display from only a few images taken with the camera. Both simulative and real experiments were conducted to show the effectiveness of our method.

Proceedings - International Conference on Image Processing, ICIP
Hajime Nagahara
Hajime Nagahara

He is working on computer vision and pattern recognition. His main research interests lie in image/video recognition and understanding, as well as applications of natural language processing techniques.