Paper Info
Title
RGBD temporal resampling for real-time occlusion removal
Abstract
Occlusions disrupt the visualization of an object of interest, or target, in a real world scene. Video inpainting removes occlusions from a video stream by cutting out occluders and filling in with a plausible visualization of the object, but the approach is too slow for real-time performance. In this paper, we present a method for realtime occlusion removal in the visualization of a real world scene that is captured with an RGBD stream. Our pipeline segments the current RGBD frame to find the target and the occluders, searches for the best matching disoccluded view of the target in an earlier frame, computes a mapping between the target in the current frame and the target in the best matching frame, inpaints the missing pixels of the target in the current frame by resampling from the earlier frame, and visualizes the disoccluded target in the current frame. We demonstrate our method in the case of a walking human occluded by stationary or walking humans. Our method does not rely on a known 2D or 3D model of the target or of the occluders, and therefore it generalizes to other shapes. Our method runs at an interactive frame rate of 30fps.
Year
DOI
Venue
2019
10.1145/3306131.3317025
Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
Keywords
Field
DocType
RGBD video, impostor, occlusion management
Computer vision,Occlusion,Computer science,Visualization,Filling-in,Inpainting,Artificial intelligence,Frame rate,Pixel,Resampling
Conference
ISBN
Citations 
PageRank 
978-1-4503-6310-5
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Wu, Meng-Lin192.14
Voicu Popescu234841.35