Advanced Real-Time Manipulation of Video Streams by Jan Herling

By Jan Herling

Diminished fact is a brand new attention-grabbing know-how that gets rid of real-world content material from reside video streams. This sensational reside video manipulation really gets rid of genuine items and generates a coherent video circulate in real-time. audience can't realize transformed content material. present techniques are constrained to relocating gadgets and static or nearly static cameras and don't permit real-time manipulation of video content material. Jan Herling offers a brand new and cutting edge strategy for real-time item elimination with arbitrary digicam movements.

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By Jan Herling

Diminished fact is a brand new attention-grabbing know-how that gets rid of real-world content material from reside video streams. This sensational reside video manipulation really gets rid of genuine items and generates a coherent video circulate in real-time. audience can't realize transformed content material. present techniques are constrained to relocating gadgets and static or nearly static cameras and don't permit real-time manipulation of video content material. Jan Herling offers a brand new and cutting edge strategy for real-time item elimination with arbitrary digicam movements.

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Extra info for Advanced Real-Time Manipulation of Video Streams

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This approach is the sole video inpainting approach dependent on camera movement as this approach does not work using a static camera. 3 Herling and Broll 2010 The approaches presented above do not aim to achieve video frame manipulation in real-time performance. Our previous approach [40] has been developed to overcome the real-time restriction. The approach was inspired by the image inpainting approach of Wexler et al. [102] and Barnes et al. [8]. A contour tracking approach for detection of objects in almost homogenous environments has been applied to remove static objects in the live video stream of a hand-held camera.

Sun et al. propose to recover the user-defined lines or curves by overlapping small image patches stringed on a chain. These patches are taken from the remaining image information, similar to Criminisi’s approach. A graph optimization algorithm is used to select best matching patches. Sun et al. remove seams between overlapping patches using a gradient-based interpolation (by application of Poisson blending [79]). 12b. In the second stage, the remaining regions are recovered using the previously described approaches of Ashikhmin [2], Drori et al.

4 Image Manipulation In the following subsection, recent image synthesis approaches are introduced to manipulate image content not only by image inpainting but also by image reshuffling or image resizing. 1 Patch-based Similarity by Simakov et al. 2009 Simakov et al. proposed a patch-based approach to manipulate images by iteratively updating the image content. They define a bidirectional dissimilarity function d(S, T ) giving a global measurement value to the visual dissimilarity of two images S(ource) and T (arget) with arbitrary dimensions.

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