• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 277,254
Next 10 →

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 495 (4 self) - Add to MetaCart
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

Chebyshev and Fourier Spectral Methods

by John P. Boyd , 1999
"... ..."
Abstract - Cited by 778 (12 self) - Add to MetaCart
Abstract not found

Content-based image retrieval at the end of the early years

by Arnold W. M. Smeulders, Marcel Worring, Simone Santini, Amarnath Gupta, Ramesh Jain - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2000
"... The paper presents a review of 200 references in content-based image retrieval. The paper starts with discussing the working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap. Subsequent sections discuss computational steps for imag ..."
Abstract - Cited by 1594 (24 self) - Add to MetaCart
The paper presents a review of 200 references in content-based image retrieval. The paper starts with discussing the working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap. Subsequent sections discuss computational steps

Image registration methods: a survey

by Barbara Zitová, Jan Flusser - IMAGE AND VISION COMPUTING , 2003
"... This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align t ..."
Abstract - Cited by 734 (9 self) - Add to MetaCart
two images (the reference and sensed images). The reviewed approaches are classified according to their nature (areabased and feature-based) and according to four basic steps of image registration procedure: feature detection, feature matching, mapping function design, and image transformation

Economic analysis of cross section and panel data

by Jeffrey M. Wooldridge
"... ..."
Abstract - Cited by 3292 (18 self) - Add to MetaCart
Abstract not found

The Elements of Statistical Learning -- Data Mining, Inference, and Prediction

by Trevor Hastie, Robert Tibshirani, Jerome Friedman
"... ..."
Abstract - Cited by 1320 (13 self) - Add to MetaCart
Abstract not found

VisualSEEk: a fully automated content-based image query system

by John R. Smith, Shih-fu Chang , 1996
"... 1 We describe a highly functional prototype system for searching by visual features in an image database. The VisualSEEk system is novel in that the user forms the queries by diagramming spatial arrangements of color regions. The system finds the images that contain the most similar arrangements of ..."
Abstract - Cited by 752 (31 self) - Add to MetaCart
be computed. KEYWORDS: image databases, content-based retrieval, image indexing, similarity retrieval, spatial query. 1 INTRODUCTION In this paper we investigate a new content-based image query system that enables querying by image regions and spatial layout. VisualSEEk is a hybrid system

High confidence visual recognition of persons by a test of statistical independence

by John G. Daugman - IEEE Trans. on Pattern Analysis and Machine Intelligence , 1993
"... Abstruct- A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a samp ..."
Abstract - Cited by 596 (8 self) - Add to MetaCart
Abstruct- A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a

Real-time human pose recognition in parts from single depth images

by Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, Andrew Blake - In In CVPR, 2011. 3
"... We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler p ..."
Abstract - Cited by 550 (19 self) - Add to MetaCart
We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler

Efficient and Effective Querying by Image Content

by C. Faloutsos, W. Equitz, M. Flickner, W. Niblack, D. Petkovic, R. Barber - Journal of Intelligent Information Systems , 1994
"... In the QBIC (Query By Image Content) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include med ..."
Abstract - Cited by 500 (13 self) - Add to MetaCart
In the QBIC (Query By Image Content) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include
Next 10 →
Results 1 - 10 of 277,254
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University