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Adaptive Reconstruction using Multiple Views
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9091-4724
1998 (English)Report (Other academic)
Abstract [en]

This report introduces a signal processing strategy for depth segmentation and scene reconstruction that incorporates occlusion as a natural component. The work aims to maximize the use of connectivity in the temporal domain as much as possible under the condition that the scene is static and that the camera motion is known. An object behind the foreground is reconstructed using the fact that different parts of the object have been seen in different images in the sequence. One of the main ideas in the reported work is the use of a spatiotemporal certainty volume c(x) with the same dimension as the input spatiotemporal volume s(x), and then use c(x) as a 'blackboard' for rejecting already segmented image structures. The segmentation starts with searching for image structures in the foreground, eliminates their occluding influence, and then proceeds. Normalized convolution, which is a Weighted Least Mean Square technique for filtering data with varying spatial reliability, is used for all filtering. High spatial resolution near object borders is achieved and only neighboring structures with similar depth supports each other.

Place, publisher, year, edition, pages
Linköping, Sweden: Linköping University, Department of Electrical Engineering , 1998. , 16 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2036
Keyword [en]
Optical flow, Translating camera, Signal model
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-53374ISRN: LiTH-ISY-R-2036OAI: diva2:288324
Available from: 2010-01-20 Created: 2010-01-20 Last updated: 2014-10-08Bibliographically approved

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Granlund, Gösta H.Knutsson, Hans
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