Results 1 - 10 of 1,713

Imagenet: A large-scale hierarchical image database

by Jia Deng, Wei Dong, Richard Socher, Li-jia Li, Kai Li, Li Fei-fei - In CVPR , 2009
"... The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images and multimedia data. But exactly how such data can be harnessed and organized remains a critical problem. We introduce her ..."
Abstract - Cited by 840 (28 self) - Add to MetaCart
datasets. Constructing such a large-scale database is a challenging task. We describe the data collection scheme with Amazon Mechanical Turk. Lastly, we illustrate the usefulness of ImageNet through three simple applications in object recognition, image classification and automatic object clustering. We

Distinctive Image Features from Scale-Invariant Keypoints

by David G. Lowe , 2003
"... This paper presents a method for extracting distinctive invariant features from images, which can be used to perform reliable matching between different images of an object or scene. The features are invariant to image scale and rotation, and are shown to provide robust matching across a a substa ..."
Abstract - Cited by 8955 (21 self) - Add to MetaCart
substantial range of affine distortion, addition of noise, change in 3D viewpoint, and change in illumination. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. This paper also

Scalable Recognition with a Vocabulary Tree

by David Nistér, Henrik Stewénius - IN CVPR , 2006
"... A recognition scheme that scales efficiently to a large number of objects is presented. The efficiency and quality is exhibited in a live demonstration that recognizes CD-covers from a database of 40000 images of popular music CD's. The scheme ..."
Abstract - Cited by 1051 (0 self) - Add to MetaCart
A recognition scheme that scales efficiently to a large number of objects is presented. The efficiency and quality is exhibited in a live demonstration that recognizes CD-covers from a database of 40000 images of popular music CD's. The scheme

Local features and kernels for classification of texture and object categories: a comprehensive study

by J. Zhang, S. Lazebnik, C. Schmid - International Journal of Computer Vision , 2007
"... Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations an ..."
Abstract - Cited by 653 (34 self) - Add to MetaCart
Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations

Similarity search in high dimensions via hashing

by Aristides Gionis, Piotr Indyk, Rajeev Motwani , 1999
"... The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing interest in building search/index structures for performing similarity search over high-dimensional data, e.g., image dat ..."
Abstract - Cited by 641 (10 self) - Add to MetaCart
The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing interest in building search/index structures for performing similarity search over high-dimensional data, e.g., image

An affine invariant interest point detector

by Krystian Mikolajczyk, Cordelia Schmid - In Proceedings of the 7th European Conference on Computer Vision , 2002
"... Abstract. This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such transformations introduce significant changes in the point location as well as in the scale and the shape of ..."
Abstract - Cited by 1467 (55 self) - Add to MetaCart
Abstract. This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such transformations introduce significant changes in the point location as well as in the scale and the shape

Histograms of Oriented Gradients for Human Detection

by Navneet Dalal, Bill Triggs - In CVPR , 2005
"... We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally that grids of Histograms of Oriented Gradient (HOG) descriptors significantly out ..."
Abstract - Cited by 3735 (9 self) - Add to MetaCart
are all important for good results. The new approach gives near-perfect separation on the original MIT pedestrian database, so we introduce a more challenging dataset containing over 1800 annotated human images with a large range of pose variations and backgrounds. 1

How Iris Recognition Works

by John Daugman , 2003
"... Algorithms developed by the author for recogniz-ing persons by their iris patterns have now been tested in six field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statis-tical independence on iris phase st ..."
Abstract - Cited by 509 (4 self) - Add to MetaCart
with extremely high confidence. The high confidence levels are important because they al-low very large databases to be searched exhaustively (one-to-many “identification mode”) without making any false matches, despite so many chances. Biomet-rics lacking this property can only survive one-to-one (“verification

Modeling annotated data

by David M. Blei, Michael I. Jordan - IN PROC. OF THE 26TH INTL. ACM SIGIR CONFERENCE , 2003
"... We consider the problem of modeling annotated data—data with multiple types where the instance of one type (such as a caption) serves as a description of the other type (such as an image). We describe three hierarchical probabilistic mixture models that are aimed at such data, culminating in the Cor ..."
Abstract - Cited by 443 (12 self) - Add to MetaCart
We consider the problem of modeling annotated data—data with multiple types where the instance of one type (such as a caption) serves as a description of the other type (such as an image). We describe three hierarchical probabilistic mixture models that are aimed at such data, culminating

Lost in quantization: Improving particular object retrieval in large scale image databases

by James Philbin, Michael Isard, Josef Sivic, Andrew Zisserman - In CVPR , 2008
"... The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local regions of images are characterized using high-dimensional descriptors which are then mapped to “visual words ” selected ..."
Abstract - Cited by 253 (8 self) - Add to MetaCart
The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local regions of images are characterized using high-dimensional descriptors which are then mapped to “visual words ” selected
Results 1 - 10 of 1,713