Title

Tri-View Morphing

Keywords

4D video; Augmented reality; Dynamic view morphing; Image-based rendering; Multi-image processing; Multiple view morphing; Trifocal geometry; Trinocular-stereo

Abstract

This paper presents an efficient image-based approach to navigate a scene based on only three wide-baseline uncalibrated images without the explicit use of a 3D model. After automatically recovering corresponding points between each pair of images, an accurate trifocal plane is extracted from the trifocal tensor of these three images. Next, based on a small number of feature marks using a friendly GUI, the correct dense disparity maps are obtained by using our trinocular-stereo algorithm. Employing the barycentric warping scheme with the computed disparity, we can generate an arbitrary novel view within a triangle spanned by three camera centers. Furthermore, after self-calibration of the cameras, 3D objects can be correctly augmented into the virtual environment synthesized by the tri-view morphing algorithm. Three applications of the tri-view morphing algorithm are demonstrated. The first one is 4D video synthesis, which can be used to fill in the gap between a few sparsely located video cameras to synthetically generate a video from a virtual moving camera. This synthetic camera can be used to view the dynamic scene from a novel view instead of the original static camera views. The second application is multiple view morphing, where we can seamlessly fly through the scene over a 2D space constructed by more than three cameras. The last one is dynamic scene synthesis using three still images, where several rigid objects may move in any orientation or direction. After segmenting three reference frames into several layers, the novel views in the dynamic scene can be generated by applying our algorithm. Finally, the experiments are presented to illustrate that a series of photo-realistic virtual views can be generated to fly through a virtual environment covered by several static cameras. © 2004 Elsevier Inc. All rights reserved.

Publication Date

1-1-2004

Publication Title

Computer Vision and Image Understanding

Volume

96

Issue

3 SPEC. ISS.

Number of Pages

345-366

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.cviu.2004.03.014

Socpus ID

7444232607 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/7444232607

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