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A Web-based System for Retrieving Document Images from Digital Library

A Web-based System for Retrieving Document Images from Digit...

引用

conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Zhang, Li Lu, Yue Tan, Chew Lim Department of Computer Science School of Computing National University of Singapore Kent Ridge Singapore117543 Singapore

ISBN: (纸本)0769519008

A web-based system for retrieving imaged documents from a digital library is described in this paper. First, some image preprocessing is performed off-line on the underlying imaged document to extract its word objects. Then, each word object is represented by a string known as its feature code, based on which a feature code file of the corresponding document is constructed. On the web interface side, the system allows the user to input a set of query words and indicate either to perform "AND" or "OR" operation on them. Once receiving user's request, the system will process each query word and combine the results based on the "AND" or "OR" operation the user has chosen. As for each query word, it is first looked up in an index table that stores words being queried before. If matches are found, results will be retrieved from the index table directly and stored temporarily for subsequent merging. This speeds up searching and makes the system an incremental intelligence system. Otherwise, the system will convert the query word to a feature code string and employ a partial word matching approach to perform search on the pre-generated feature code files. Preliminary experimental results with the imaged documents of students' theses provided by our digital library show that the proposed system is efficient and promising for document image retrieval, and thus has potential applications to digital libraries. © 2003 IEEE.

关键词： Digital libraries

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Real Time Face Detection and Facial Expression recognition: Development and Applications to Human computer Interaction

Real Time Face Detection and Facial Expression Recognition: ...

引用

conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Bartlett, Marian Stewart Littlewort, Gwen Fasel, Ian Movellan, Javier R. Machine Perception Laboratory Institute for Neural Computation University of California San DiegoCA92093 United States Intelligent Robotics and Communication Laboratories ATR Kyoto Japan

ISBN: (纸本)0769519008

computer animated agents and robots bring a social dimension to human computer interaction and force us to think in new ways about how computers could be used in daily life. Face to face communication is a real-time process operating at a a time scale in the order of 40 milliseconds. The level of uncertainty at this time scale is considerable, making it necessary for humans and machines to rely on sensory rich perceptual primitives rather than slow symbolic inference processes. In this paper we present progress on one such perceptual primitive. The system automatically detects frontal faces in the video stream and codes them with respect to 7 dimensions in real time: neutral, anger, disgust, fear, joy, sadness, surprise. The face finder employs a cascade of feature detectors trained with boosting techniques [15, 2]. The expression recognizer receives image patches located by the face detector. A Gabor representation of the patch is formed and then processed by a bank of SVM classifiers. A novel combination of Adaboost and SVM's enhances performance. The system was tested on the Cohn-Kanade dataset of posed facial expressions [6]. The generalization performance to new subjects for a 7- way forced choice correct. Most interestingly the outputs of the classifier change smoothly as a function of time, providing a potentially valuable representation to code facial expression dynamics in a fully automatic and unobtrusive manner. The system has been deployed on a wide variety of platforms including Sony's Aibo pet robot, ATR's RoboVie, and CU animator, and is currently being evaluated for applications including automatic reading tutors, assessment of human-robot interaction. © 2003 IEEE.

关键词： Adaptive boosting

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A Statistical Assessment of Subject Factors in the PCA recognition of Human Faces

A Statistical Assessment of Subject Factors in the PCA Recog...

引用

conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Givens, Geof Beveridge, J Ross Draper, Bruce A. Bolme, David Statistics Department Colorado State University Fort CollinsCO United States Computer Science Department Colorado State University Fort CollinsCO United States

ISBN: (纸本)0769519008

Some people's faces are easier to recognize than others, but it is not obvious what subject-specific factors make individual faces easy or difficult to recognize. This study considers 11 factors that might make recognition easy or difficult for 1,072 human subjects in the FERET dataset. The specific factors are: race (white, Asian, African-American, or other), gender, age (young or old), glasses (present or absent), facial hair (present or absent), bangs (present or absent), mouth (closed or other), eyes (open or other), complexion (clear or other), makeup (present or absent), and expression (neutral or other). An ANOVA is used to determine the relationship between these subject covariates and the distance between pairs of images of the same subject in a standard Eigenfaces subspace. Some results are not terribly surprising. For example, the distance between pairs of images of the same subject increases for people who change their appearance, e.g., open and close their eyes, open and close their mouth or change expression. Thus changing appearance makes recognition harder. Other findings are surprising. Distance between pairs of images for subjects decreases for people who consistently wear glasses, so wearing glasses makes subjects more recognizable. Pairwise distance also decreases for people who are either Asian or African-American rather than white. A possible shortcoming of our analysis is that minority classifications such as African-Americans and wearers-of-glasses are underrepresented in training. Followup experiments with balanced training addresses this concern and corroborates the original findings. Another possible shortcoming of this analysis is the novel use of pairwise distance between images of a single person as the predictor of recognition difficulty. A separate experiment confirms that larger distances between pairs of subject images implies a larger recognition rank for that same pair of images, thus confirming that the subject is harder to recog

关键词： Glass

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Learning and Perceptual Interfaces

Learning and Perceptual Interfaces

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： T. Poggio Center for Biological and Computational Learning Artificial Intelligence Laboratory and McGovern Institute for Brain Research M.I.T. USA

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Higher-order Wavelet Statistics and their Application to Digital Forensics

Higher-order Wavelet Statistics and their Application to Dig...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Hany Farid Siwei Lyu Sudikoff Laboratory Department of Computer Science Dartmouth College Hanover NH USA

We describe a statistical model for natural images that is built upon a multi-scale wavelet decomposition. The model consists of first- and higher-order statistics that capture certain statistical regularities of natural images. We show how this model can be useful in several digital forensic applications, specifically in detecting various types of digital tampering.

关键词： Vectors computer graphics Noise conferences computer vision pattern recognition Computational modeling

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Drawing Accurate Ground Plans Using Optical Triangulation Data

Drawing Accurate Ground Plans Using Optical Triangulation Da...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Kevin Cain Philippe Martinez INSIGHT Έcole normale supérieure INSIGHT France

Here we consider optical triangulation scanning as a means of creating permanent architectural archives in the form of accurate ground plans and other orthographic views. We present plan drawings created with laser scan data and use these documents to make comparisons with existing documents. Finally, we present a new technique for decreasing the laser scanning field time required to create plans and other views.

关键词： conferences computer vision pattern recognition

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Robust Fusion of Uncertain Information

Robust Fusion of Uncertain Information

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Haifeng Chen Peter Meer Electrical and Computer Engineering Rutgers University Piscataway NJ USA

A technique is presented to combine n data points, each available with point-dependent uncertainty, when only a subset of these points come from N \ll n sources, where N is unknown. We detect the significant modes of the underlying multivariate probability distribution using a generalization of the nonparametric mean shift procedure. The number of detected modes automatically defiens N, while the appurtenance of a point to the basin of attraction of a mode provides the fusion rule.

关键词： conferences computer vision pattern recognition

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Mathematics of a Multiple Omni-Directional System

Mathematics of a Multiple Omni-Directional System

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： A. Torii A. Sugimoto A. Imiya School of Science and Technology Chiba University Japan National Institute of Informatics Japan National Institute of Information Japan Institute of Media and Information Technology Chiba University Japan

We formulate multiple-view geometry for omni-directional and panorama-camera systems. The mathematical formu-lations enable us to derive the geometrical and algebraic constraints for multiple panorama-camera configura... 详细信息

关键词： Cameras Mathematical model Geometry Equations Stereo vision Computational modeling computer vision

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Time-dependent HMMs for visual intrusion detection

Time-dependent HMMs for visual intrusion detection

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Vera M. Kettnaker Rensselaer Polytechnic Institute Troy NY USA

We propose a new Hidden Markov Model with time-dependent states. Estimation of this model is shown to be as fast and easy as the estimation of regular HMMs. We demonstrate the usefulness and feasibility of such time-dependent HMMs with an application in which illegitimate access to personnel-only rooms in airports etc. can be distinguished from access by legitimate personnel, based on differences in the time of access or differences in the motion trajectories.

关键词： Hidden Markov models Computational modeling Estimation Pixel Security computer vision conferences

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Learning Visual Feature Detectors for Obstacle Avoidance using Genetic Programming

Learning Visual Feature Detectors for Obstacle Avoidance usi...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Andrew Marek William D. Smart Martin C. Martin Department of Computer Science and Engineering Washington University Saint Louis MO USA MIT Artificial Intelligence Laboratory Cambridge MA USA

In this paper, we describe the use of Genetic Programming (GP) techniques to learn a visual feature detection for a mobile robot navigation task. We provide experimental results across a number of different environments, each with different characteristics, and draw conclusions about the performance of the learned feature detector. We also explore the utility of seeding the initial population with a previously evolved individual, and discuss the performance of the resulting individuals.

关键词： Feature extraction Pixel Training conferences Robots computer vision pattern recognition

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