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Stereo matching and volumetric reconstruction are the most explored 3D scene recovery techniques in computer vision. Many existing approaches assume perspective input images and use the epipolar constraint to reduce the search space and improve the accuracy. In this paper we present a novel framework that uses multi-perspective cameras for stereo matching and volumetric reconstruction. Our approach...
We present a new shape-from-distortion framework for recovering specular (reflective/refractive) surfaces. While most existing approaches rely on accurate correspondences between 2D pixels and 3D points, we focus on analyzing the curved images of 3D lines which we call curved line images or CLIs. Our approach models CLIs of local reflections or refractions using the recently proposed general linear...
We present a catadioptric projector analogous to a catadioptric camera by combining a commodity digital projector with additional optical units. We show that, by using specially shaped reflectors/refractors, catadioptric projectors can offer an unprecedented level of flexibility in aspect ratio, size, and field of view. We also present efficient algorithms to reduce projection artifacts in catadioptric...
We present a hybrid camera that combines the advantages of a high resolution camera and a high speed camera. Our hybrid camera consists of a pair of low-resolution high-speed (LRHS) cameras and a single high-resolution low-speed (HRLS) camera. The LRHS cameras are able to capture fast-motion with little motion blur. They also form a stereo pair and provide a low-resolution depth map. The HRLS camera...
In this paper, we present a novel single-image vignetting method based on the symmetric distribution of the radial gradient (RG). The radial gradient is the image gradient along the radial direction with respect to the image center. We show that the RG distribution for natural images without vignetting is generally symmetric. However, this distribution is skewed by vignetting. We develop two variants...
In this paper, we propose an online interactive matting algorithm, which we call FuzzyMatte. Our framework is based on computing the fuzzy connectedness (FC) from each unknown pixel to the known foreground and background. FC effectively captures the adjacency and similarity between image elements and can be efficiently computed using the strongest connected path searching algorithm. The final alpha...
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