DocumentCode
145499
Title
[Poster] Motion detection based ghosted views for occlusion handling in augmented reality
Author
Padilha, Arthur ; Teichrieb, Veronica
Author_Institution
Voxar Labs., Fed. Univ. of Pernambuco, Recife, Brazil
fYear
2014
fDate
10-12 Sept. 2014
Firstpage
291
Lastpage
292
Abstract
This work presents an improvement to the scene analysis pipeline of a visualization technique called Ghosting. Computer vision and image processing techniques are used to extract natural features, from each video frame. These features will guide the assignment of transparency to pixels, in order to give the ghosting effect, while blending the virtual object into the real scene. Video sequences were obtained from traditional RGB cameras. The main contribution of this work is the inclusion of a motion detection technique to the scene feature analysis step. This procedure leads to a better perception of the augmented scene because the proper ghosting effect is achieved when a moving natural salient object, that catches users attention, passes in front of an augmented one.
Keywords
augmented reality; computer vision; feature extraction; image motion analysis; image sequences; object detection; video signal processing; augmented reality; computer vision; feature extraction; ghosting technique; image processing techniques; motion detection based ghosted view; moving natural salient object; occlusion handling; scene analysis pipeline; scene feature analysis; video sequences; visualization technique; Augmented reality; Computer vision; Feature extraction; Image analysis; Motion detection; Pipelines; Visualization; H.5.1 [Information Interfaces and Presentation Systems]: Multimedia Information Systems — Artificial, augmented, virtual realities; I.4.8 [Image Processing and Computer Vision]: Scene Analysis — Depth cues;
fLanguage
English
Publisher
ieee
Conference_Titel
Mixed and Augmented Reality (ISMAR), 2014 IEEE International Symposium on
Conference_Location
Munich
Type
conf
DOI
10.1109/ISMAR.2014.6948455
Filename
6948455
Link To Document