27,807 research outputs found

    Photo repair and 3d structure from flatbed scanners

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    We introduce a technique that allows 3D information to be captured from a conventional flatbed scanner. The technique requires no hardware modification and allows untrained users to easily capture 3D datasets. Once captured, these datasets can be used for interactive relighting and enhancement of surface detail on physical objects. We have also found that the method can be used to scan and repair damaged photographs. Since the only 3D structure on these photographs will typically be surface tears and creases, our method provides an accurate procedure for automatically detecting these flaws without any user intervention. Once detected, automatic techniques, such as infilling and texture synthesis, can be leveraged to seamlessly repair such damaged areas. We first present a method that is able to repair damaged photographs with minimal user interaction and then show how we can achieve similar results using a fully automatic process

    HeadOn: Real-time Reenactment of Human Portrait Videos

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    We propose HeadOn, the first real-time source-to-target reenactment approach for complete human portrait videos that enables transfer of torso and head motion, face expression, and eye gaze. Given a short RGB-D video of the target actor, we automatically construct a personalized geometry proxy that embeds a parametric head, eye, and kinematic torso model. A novel real-time reenactment algorithm employs this proxy to photo-realistically map the captured motion from the source actor to the target actor. On top of the coarse geometric proxy, we propose a video-based rendering technique that composites the modified target portrait video via view- and pose-dependent texturing, and creates photo-realistic imagery of the target actor under novel torso and head poses, facial expressions, and gaze directions. To this end, we propose a robust tracking of the face and torso of the source actor. We extensively evaluate our approach and show significant improvements in enabling much greater flexibility in creating realistic reenacted output videos.Comment: Video: https://www.youtube.com/watch?v=7Dg49wv2c_g Presented at Siggraph'1
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