Prof. Jae-Young Sim (Ulsan National Institute of Science and Technology (UNIST), Korea)

Lecture 5

Glass Reflection Removal for Images and 3D Point Clouds

Abstract

We often capture images and 3D point clouds of a target scene through glass. The captured data may include undesired reflection artifacts since light passes through and is reflected on a pane of glass simultaneously. Such reflection artifacts may degrade the performance of image processing and computer vision techniques. In this lecture, we talk about our research work on automatic reflection removal for images and 3D point clouds. We first propose reflection removal algorithms for images. We consider multiple glass images and separate the transmission and reflection images by restoring the gradients of the transmission images via low-rank matrix completion. We also propose a semantic based reflection removal network for a single glass image that investigates a non-linear intensity mapping for glass images. Next, we introduce the reflection removal algorithm for large-scale 3D point clouds (LS3DPCs) captured by LiDAR scanners. We estimate multiple glass regions by using the characteristics of LiDAR. Then we detect virtual points by recursively traversing the possible trajectories of light reflection and selecting the optimal trajectory satisfying reflection symmetry and geometric similarity.