Brandon M. Smith

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We propose a novel formulation of stereo matching that considers each pixel as a feature vector. Under this view, matching two or more images can be cast as matching point clouds in feature space. We build a nonparametric depth smoothness model in this space that correlates the image features and depth values. This model induces a sparse graph that links(More)
Figure 1 shows a visual overview of our pipeline, and supplements Section 3 of our paper. Figures 2, 3, and 4 supplement Figure 3 in our paper. The input images in Figure 2 are from the AFW dataset [3], and the input images in Figure 3 are from the IBUG dataset [2]. We note that our algorithm generally produces accurate results, even on faces with extreme(More)
We describe a method for producing a smooth, stabilized video from the shaky input of a hand-held light field video camera — specifically, a small camera array. Traditional stabilization techniques dampen shake with 2D warps, and thus have limited ability to stabilize a significantly shaky camera motion through a 3D scene. Other recent stabilization(More)
In this paper, we present a new framework for non-rigid structure from motion (NRSFM) that simultaneously addresses three significant challenges: severe occlusion, perspective camera projection, and large non-linear deformation. We introduce a concept called a model graph, which greatly reduces the computational cost of discovering groups of input images(More)
In this work, we propose an exemplar-based face image segmentation algorithm. We take inspiration from previous works on image parsing for general scenes. Our approach assumes a database of exemplar face images, each of which is associated with a hand-labeled segmentation map. Given a test image, our algorithm first selects a subset of exemplar images from(More)
In this paper we make the first effort, to the best of our knowledge, to combine multiple face landmark datasets with different landmark definitions into a super dataset, with a union of all landmark types computed in each image as output. Our approach is flexible, and our system can optionally use known landmarks in the target dataset to constrain the(More)
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