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Saliency, Scale and Image Description

by Timor Kadir, Michael Brady , 2001
"... Many computer vision problems can be considered to consist of two main tasks: the extraction of image content descriptions and their subsequent matching. The appropriate choice of type and level of description is of course task dependent, yet it is generally accepted that the low-level or so called ..."
Abstract - Cited by 239 (0 self) - Add to MetaCart
Many computer vision problems can be considered to consist of two main tasks: the extraction of image content descriptions and their subsequent matching. The appropriate choice of type and level of description is of course task dependent, yet it is generally accepted that the low-level or so

image description

by Guillaume Joutel, Véronique Eglin, Hubert Emptoz
"... complete pyramidal geometrical scheme for text based ..."
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complete pyramidal geometrical scheme for text based

Image description with . . .

by J. J. Corso, G. D. Hager - COMPUTER VISION AND IMAGE UNDERSTANDING 113 (2009) 446–458 , 2009
"... ..."
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Abstract not found

Image description

by Xiradiol Bras Nov/dez ():xi–xiii, Misael Gadelha Terceiro, Igor Murad Faria, Rafael Alfenas De Paula, Edson Marchiori, Xii Radiol
"... A 72-year-old, female patient presented with abdomi-nal pain in the right flank for two days. Physical examina-tion revealed pain at palpation and painful decompression, particularly in the right lower quadrant of the abdomen. ..."
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A 72-year-old, female patient presented with abdomi-nal pain in the right flank for two days. Physical examina-tion revealed pain at palpation and painful decompression, particularly in the right lower quadrant of the abdomen.

Classification of User Image Descriptions

by L. Hollink , A. Th. Schreiber, B.J. Wielinga, M. Worring , 2004
"... In order to resolve the mismatch between user needs and current image retrieval techniques, we conducted a study to get more information about what users look for in images. First, we developed a framework for the classification of image descriptions by users, based on various classification methods ..."
Abstract - Cited by 33 (3 self) - Add to MetaCart
In order to resolve the mismatch between user needs and current image retrieval techniques, we conducted a study to get more information about what users look for in images. First, we developed a framework for the classification of image descriptions by users, based on various classification

Face description with local binary patterns: Application to face recognition

by Abdenour Hadid, Senior Member - IEEE Trans. Pattern Analysis and Machine Intelligence , 2006
"... Abstract—This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a ..."
Abstract - Cited by 526 (27 self) - Add to MetaCart
Abstract—This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a

Labeling Images with a Computer Game

by Luis Von Ahn , 2004
"... We introduce a new interactive system: a game that is fun and can be used to create valuable output. When people play the game they help determine the contents of images by providing meaningful labels for them. If the game is played as much as popular online games, we estimate that most images on ..."
Abstract - Cited by 773 (11 self) - Add to MetaCart
on the Web can be labeled in a few months. Having proper labels associated with each image on the Web would allow for more accurate image search, improve the accessibility of sites (by providing descriptions of images to visually impaired individuals), and help users block inappropriate images. Our system

Photobook: Content-Based Manipulation of Image Databases

by A. Pentland, R. W. Picard, S. Sclaroff , 1995
"... We describe the Photobook system, which is a set of interactive tools for browsing and searching images and image sequences. These query tools differ from those used in standard image databases in that they make direct use of the image content rather than relying on text annotations. Direct search o ..."
Abstract - Cited by 542 (0 self) - Add to MetaCart
on image content is made possible by use of semantics-preserving image compression, which reduces images to a small set of perceptually-significant coefficients. We describe three types of Photobook descriptions in detail: one that allows search based on appearance, one that uses 2-D shape, and a third

Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories

by Cordelia Schmid - In CVPR
"... This paper presents a method for recognizing scene categories based on approximate global geometric correspondence. This technique works by partitioning the image into increasingly fine sub-regions and computing histograms of local features found inside each sub-region. The resulting “spatial pyrami ..."
Abstract - Cited by 1923 (47 self) - Add to MetaCart
and achieves high accuracy on a large database of fifteen natural scene categories. The spatial pyramid framework also offers insights into the success of several recently proposed image descriptions, including Torralba’s “gist ” and Lowe’s SIFT descriptors. 1.

Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression

by John G. Daugman , 1988
"... A three-layered neural network is described for transforming two-dimensional discrete signals into generalized nonorthogonal 2-D “Gabor” representations for image analysis, segmentation, and compression. These transforms are conjoint spatial/spectral representations [lo], [15], which provide a comp ..."
Abstract - Cited by 478 (8 self) - Add to MetaCart
complete image description in terms of locally windowed 2-D spectral coordinates embedded within global 2-D spatial coordinates. Because intrinsic redundancies within images are extracted, the resulting image codes can be very compact. However, these conjoint transforms are inherently difficult to compute
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