“Virtual point removal for large-scale 3D point clouds”
Jae-Young Sim received the B.S. degree in electrical engineering and the M.S. and Ph.D. degrees in electrical engineering and computer science from Seoul National University, Seoul, South Korea, in 1999, 2001, and 2005, respectively. From 2005 to 2009, he was a Research Staff Member with the Samsung Advanced Institute of Technology, Samsung Electronics Company, Ltd. In 2009, he joined the School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea, where he is now a Professor in Graduate School of AI and Dept. of Electrical Engineering. He is also serving as Head of UNIST AI Innovation Park and Dean of the College of Information and Biotechnology, UNIST. His research interests include image, video, and 3D visual processing and computer vision.
We often capture images of a target scene through glass. For example, we take photographs of the products displayed in the show window, or take photographs of buildings with glass curtain walls. The captured glass image includes the target scene behind the glass as well as undesired reflected scene in front of the glass, since light passes through and is reflected on a pane of glass simultaneously. Also, with the advent of high-performance LiDAR scanners, large-scale 3D point clouds (LS3DPCs) for real-world scenes are being used in challenging applications. However, LS3DPCs captured by terrestrial LiDAR scanners also suffer from the reflection artifacts since many outdoor real-world structures include glasses. Such reflection artifacts may degrade the performance of image processing and computer vision techniques when applied to glass images. In this seminar, we first define a problem of reflection in LS3DPCs, and introduce automatic reflection removal algorithms for LS3DPCs.
ZOOM : https://zoom.us/j/8978217407?pwd=d1pOZmF1OWlseEdZRVBpV3VuSkl3dz09