T
Thomas S. Huang
Researcher at University of Illinois at Urbana–Champaign
Publications - 1311
Citations - 111898
Thomas S. Huang is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Motion estimation & Facial recognition system. The author has an hindex of 146, co-authored 1299 publications receiving 101564 citations. Previous affiliations of Thomas S. Huang include Alcatel-Lucent & National Academy of Engineering.
Papers
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Journal ArticleDOI
Image Super-Resolution Via Sparse Representation
TL;DR: This paper presents a new approach to single-image superresolution, based upon sparse signal representation, which generates high-resolution images that are competitive or even superior in quality to images produced by other similar SR methods.
Journal ArticleDOI
Least-Squares Fitting of Two 3-D Point Sets
TL;DR: An algorithm for finding the least-squares solution of R and T, which is based on the singular value decomposition (SVD) of a 3 × 3 matrix, is presented.
Proceedings ArticleDOI
Locality-constrained Linear Coding for image classification
TL;DR: This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM, using the locality constraints to project each descriptor into its local-coordinate system, and the projected coordinates are integrated by max pooling to generate the final representation.
Proceedings ArticleDOI
Linear spatial pyramid matching using sparse coding for image classification
TL;DR: An extension of the SPM method is developed, by generalizing vector quantization to sparse coding followed by multi-scale spatial max pooling, and a linear SPM kernel based on SIFT sparse codes is proposed, leading to state-of-the-art performance on several benchmarks by using a single type of descriptors.
Image processing
TL;DR: Parts of image processing are discussed--specifically: the mathematical operations one is likely to encounter, and ways of implementing them by optics and on digital computers; image description; and image quality evaluation.