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This paper introduces an efficient algorithm for the compressed MR image reconstruction problem, which is formulated as the minimization of a linear combination of three terms corresponding to a least square data fitting, nonlocal total variation (NLTV) and wavelet sparsity regularization. In our method, the original minimization problem is decomposed into(More)
A Reverse k-Nearest-Neighbor (RkNN) query finds the objects that take the query object as one of their k nearest neighbors. In this paper we propose new solutions for evaluating RkNN queries and its variant bichromatic RkNN queries on 2-dimensional location data. We present an algorithm named INCH that can compute a RkNN query's search region (from which(More)
— This paper presents a new eye localization method via Multiscale Sparse Dictionaries (MSD). We built a pyramid of dictionaries that models context information at multiple scales. Eye locations are estimated at each scale by fitting the image through sparse coefficients of the dictionary. By using context information, our method is robust to various eye(More)
We address the problem of correcting an undesirable expression on a face photo by transferring local facial components, such as a smiling mouth, from another face photo of the same person which has the desired expression. Direct copying and blending using existing compositing tools results in semantically unnatural composites, since expression is a global(More)
We address the problem of editing facial expression in video, such as exaggerating, attenuating or replacing the expression with a different one in some parts of the video. To achieve this we develop a tensor-based 3D face geometry reconstruction method, which fits a 3D model for each video frame, with the constraint that all models have the same identity(More)
— This paper addresses the problem of facial landmark localization on partially occluded faces. We proposes an explicit occlusion detection based deformable fitting model for occluded landmark localization. Most recent shape registration methods apply landmark local search and attempt to simultaneously minimize both the model error and localization error.(More)
This paper addresses the problem of automatically recognizing linguistically significant nonmanual expressions in American Sign Language from video. We develop a fully automatic system that is able to track facial expressions and head movements, and detect and recognize facial events continuously from video. The main contributions of the proposed framework(More)