Ever since the release of Avatar, stereo video has gained significant attention not just in the field of computer vision. As more and more feature films exploit the illusion of depth, we propose a minimally intrusive, non-parametric and fully automated pipeline to extend the dynamic range of stereo video. Shot using two cameras, we argue that stereoscopy is an ideal candidate for high dynamic range imaging and present a novel workflow that preserves significantly more details and color in 3D video. By combining an improved stereo matching algorithm for differently exposed video frames with high dynamic range imaging, we notably enhance the contrast and the perceived quality of both video channels, while still only requiring a single simultaneous shot. The efficient use of SIFT descriptors makes this method easily adaptable to any stereoscopic footage and removes many of the drawbacks of both stereo video and traditional high dynamic range imaging.
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Sebastian Schmidt is a software engineer in San Francisco, CA. After extensive exposure to OpenGL and hardware acceleration during his undergrad degree, he spent his graduate career in Vancouver, BC to work on cutting edge technologies that for the first time bring 3D video and high dynamic range imaging together.
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Ever since the release of Avatar, stereo video has gained significant attention not just in the field of computer vision. As more and more feature films exploit the illusion of depth, we propose a minimally intrusive, non-parametric and fully automated pipeline to extend the dynamic range of stereo video. Shot using two cameras, we argue that stereoscopy is an ideal candidate for high dynamic range imaging and present a novel workflow that preserves significantly more details and color in 3D video. By combining an improved stereo matching algorithm for differently exposed video frames with high dynamic range imaging, we notably enhance the contrast and the perceived quality of both video channels, while still only requiring a single simultaneous shot. The efficient use of SIFT descriptors makes this method easily adaptable to any stereoscopic footage and removes many of the drawbacks of both stereo video and traditional high dynamic range imaging. 104 pp. Englisch. Seller Inventory # 9783639434675
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Schmidt SebastianSebastian Schmidt is a software engineer in San Francisco, CA. After extensive exposure to OpenGL and hardware acceleration during his undergrad degree, he spent his graduate career in Vancouver, BC to work on cuttin. Seller Inventory # 4987674
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Ever since the release of Avatar, stereo video has gained significant attention not just in the field of computer vision. As more and more feature films exploit the illusion of depth, we propose a minimally intrusive, non-parametric and fully automated pipeline to extend the dynamic range of stereo video. Shot using two cameras, we argue that stereoscopy is an ideal candidate for high dynamic range imaging and present a novel workflow that preserves significantly more details and color in 3D video. By combining an improved stereo matching algorithm for differently exposed video frames with high dynamic range imaging, we notably enhance the contrast and the perceived quality of both video channels, while still only requiring a single simultaneous shot. The efficient use of SIFT descriptors makes this method easily adaptable to any stereoscopic footage and removes many of the drawbacks of both stereo video and traditional high dynamic range imaging.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch. Seller Inventory # 9783639434675
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Ever since the release of Avatar, stereo video has gained significant attention not just in the field of computer vision. As more and more feature films exploit the illusion of depth, we propose a minimally intrusive, non-parametric and fully automated pipeline to extend the dynamic range of stereo video. Shot using two cameras, we argue that stereoscopy is an ideal candidate for high dynamic range imaging and present a novel workflow that preserves significantly more details and color in 3D video. By combining an improved stereo matching algorithm for differently exposed video frames with high dynamic range imaging, we notably enhance the contrast and the perceived quality of both video channels, while still only requiring a single simultaneous shot. The efficient use of SIFT descriptors makes this method easily adaptable to any stereoscopic footage and removes many of the drawbacks of both stereo video and traditional high dynamic range imaging. Seller Inventory # 9783639434675