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Videoshop: a new framework for spatio-temporal video editing in gradient domain
Wang, H.; Xu, N.; Ramesh Raskar; Narendra Ahuja;
Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on
Volume 2,
20-25 June 2005
Page(s):1201 vol. 2
Abstract:
Our goal is to develop tools that go beyond frame-constrained manipulation such as resizing, color correction, and simple transitions, and provide object-level operations within frames. Some of our targeted video editing tasks includes transferring a motion picture to a new still picture, importing a moving object into a new background, and compositing two video sequences. The challenges behind this kind of complex video editing tasks lie in two constraints: 1) Spatial consistency: imported objects should blend with the background seamlessly. Hence pixel replacement, which creates noticeable seams, is problematic. 2) Temporal coherency: successive frames should display smooth transitions. Hence frame-by-frame editing, which results in visual flicker, is inappropriate. Our work is aimed at providing an easy-to-use video editing tool that maximally satisfies the spatial and temporal constraints mentioned above and requires minimum user interaction. We propose a new framework for video editing in gradient domain. The spatio-temporal gradient fields of target videos are modified and/or mixed to generate a new gradient field which is usually not integrable. We propose a 3D video integration algorithm, which uses the variational method, to find the potential function whose gradient field is closest to the mixed gradient field in the sense of least squares. The video is reconstructed by solving a 3D Poisson equation. We derive an extension of current 2D gradient technique to 3D space, yielding in a novel video editing framework, which is very different from all current video editing software.
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