Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)
DOI: 10.1109/im.1999.805384
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Appearance-based virtual view generation of temporally-varying events from multi-camera images in the 3D room

Abstract: In this paper, we present an "appearance-based" virtual view generation method for temporally-varying events taken by multiple cameras of the "3D Room", developed by our group. With this method, we can generate images from any virtual view point between two selected real views. The virtual appearance view generation method is based on simple interpolation between two selected views. The correspondence between the views are automatically generated from the multiple images by use of the volumetric model shape re… Show more

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Cited by 31 publications
(10 citation statements)
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“…Over the last few years, cameras have become ubiquitous due to their declining costs, so that vision systems using multiple cameras are becoming cost effective. Example of multi-view vision systems include the 3D room developed by Kanade et al [19] and the Keck Laboratory (Davis et al [9]). …”
Section: Introductionmentioning
confidence: 99%
“…Over the last few years, cameras have become ubiquitous due to their declining costs, so that vision systems using multiple cameras are becoming cost effective. Example of multi-view vision systems include the 3D room developed by Kanade et al [19] and the Keck Laboratory (Davis et al [9]). …”
Section: Introductionmentioning
confidence: 99%
“…Appearance-based virtual-view synthesis [16] takes into account the advantages of MBR and IBR. This 3-D shape model, which is recovered from multiple images, provides the required information for the IBR process, such as correspondence map, occluded area, etc., for the input images.…”
Section: Related Workmentioning
confidence: 99%
“…Multi-view videos are widely used for 3-D visualization [1]- [3]. Multi-view images of a scene or an event are commonly captured by people holding different types of cameras.…”
Section: Introductionmentioning
confidence: 99%