Event Synthesis for Light Field Videos using Recurrent Neural Networks
Zhicheng Lu, Xiaoming Chen, Yuk Ying Chung, Sen Liu · 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) · 2022
Light field videos (LFVs), consisting of multiple angles of view, yield higher complexity in performing computer vision tasks. The emerging event cameras offer a new means for light-weight processing of LFVs, but it is infeasible to build an LFV capturing device with multiple event cameras due to their high costs. In this poster, we propose a novel “event synthesis for light field videos” (ES4LFV) model by using recurrent neural networks and build a preliminary dataset for training. The ES4LFV can synthesize events for light field video (E-LFV) from LFV camera array and single event camera. The experimental results show that ES4LFV outperforms the traditional method by 3.1dB in PSNR.