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检索条件"任意字段=MIPPR 2007: Pattern Recognition and Computer Vision"

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Online Learning for Human-Robot Interaction

Online Learning for Human-Robot Interaction

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Bogdan Raducanu Jordi Vitria Computer Vision Center Barcelona Spain Computer Science Department Autonomous University of Barcelona Barcelona Spain

This paper presents a novel approach for incremental subspace learning based on an online version of the non-parametric discriminant analysis (NDA). For many real-world applications (like the study of visual processes, for instance) there is impossible to know beforehand the number of total classes or the exact number of instances per class. This motivated us to propose a new algorithm, in which new samples can be added asynchronously, at different time stamps, as soon as they become available. The proposed technique for NDA-eigenspace representation has been applied to the problem of online face recognition for human-robot interaction scenario.

关键词： Face recognition Humans Feature extraction Scattering Machine vision pattern recognition Gaussian distribution Nearest neighbor searches Covariance matrix computer vision

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Introduction of New Associate Editors

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IEEE Transactions on pattern Analysis and Machine Intelligence 2007年第6期29卷 913-914页

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Hierarchical graph-based media content representation for real time search in large scale multimedia databases

Hierarchical graph-based media content representation for re...

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9th IASTED International Conference on Signal and Image Processing

作者： Papadakis, Nikos Doulamis, Nikolaos Doulamis, Anastasios Univ Crete Iraklion Greece Natl Tech Univ Athens Athens Greece

ISBN: (纸本)9780889866751

This paper presents a system architecture and the appropriate algorithms for confidential searching of multimedia digital libraries. The proposed scheme uses Middleware service layer that allows pre-processing of raw content with technology owned by the Search Engine, without compromising the security of the original architecture in any way. The specific search algorithms described are a hierarchical graph structure algorithm for preprocessing, and a backtracking search algorithm that achieves good real-time performance (speed, and precision-recall values) under the given security constraints.

关键词： pattern recognition image process computer vision

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A Benchmarking Dataset for Performance Evaluation of Automatic Surface Reconstruction Algorithms

A Benchmarking Dataset for Performance Evaluation of Automat...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Anke Bellmann Olaf Hellwich Volker Rodehorst Ulas Yilmaz Computer Vision & Remote Sensing Berlin University of Technology Berlin Germany

Numerous techniques were invented in computer vision and photogrammetry to obtain spatial information from digital images. We intend to describe and improve the performance of these vision techniques by providing test objectives, data, metrics and test protocols. In this paper we propose a comprehensive benchmarking dataset for evaluating a variety of automatic surface reconstruction algorithms (shape-from-X) and a methodology for comparing their results.

关键词： Surface reconstruction Reconstruction algorithms Calibration Robot vision systems Digital cameras CMOS image sensors Pixel computer vision Testing Image reconstruction

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Development of a computer vision binocular system for non-contact small animal model skin cancer tumour imaging

Development of a computer vision binocular system for non-co...

引用

Conference on Diffuse Optical Imaging of Tissue

作者： Gorpas, Dimitris S. Politopoulos, Kostas Yova, Dido Natl Tech Univ Athens Lab Biomed Opt & Appl Biophys Sch Elect & Comp Engn 9 Iroon Polytexneiou StrZografou Campus Zografos 15773 Greece

ISBN: (纸本)9780819467737

This paper describes the development of a novel gauging computer vision system for murine non-melanoma skin cancer tumours volume imaging. The system utilized binocular stereovision, enhanced through the use of telecentric lenses. These lenses optically compromised for the distortion factors and provided orthographic projection, leading to parallax free image acquisition. In order to improve the resolution of the system, a structured light projector, with 450 nm dominant wavelength, was used to illuminate the target with a custom pattern. Robust image processing algorithms granted accurate segmentation, feature recognition, labeling and correlation between the stereo pairs. Under these premises, the well-known "matching" problem was resolved successfully and geometrical interpolation provided an accurate three-dimensional reconstruction of the tumour volume. Through back-projection of the calibration object the resolution of the system was calculated up to 0.04 mm. The system was applied to measure the induced geometrical alterations of the tumour after PDT by using the Fosgel photosensitizer, excited by a laser diode emitting at 652 nm. The measurement of the volume induced alterations after each PDT treatment and up to the final tumour shrinkage is critical, to compare PDT efficacy between different protocols.

关键词： photogrammetry telecentric lenses matching problem non-melanoma skin cancer tumour PDT assessment

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Virtual Training for Multi-View Object Class recognition

Virtual Training for Multi-View Object Class Recognition

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Conference on computer vision and pattern recognition (CVPR)

作者： Han-Pang Chiu Leslie Pack Kaelbling Tomas Lozano-Perez MIT Computer Science and Artificial Intelligence Laboratory Cambridge MA USA

Our goal is to circumvent one of the roadblocks to using existing approaches for single-view recognition for achieving multi-view recognition, namely, the need for sufficient training data for many viewpoints. We show how to construct virtual training examples for multi-view recognition using a simple model of objects (nearly planar facades centered at fixed 3D positions). We also show how the models can be learned from a few labeled images for each class.

关键词： Skeleton Shape Training data Predictive models computer science Artificial intelligence Laboratories Machine vision Image sequences Phase estimation

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A human action classifier from 4-D data (3-D+Time) - Based on an Invariant Body Shape Descriptor and Hidden Markov Models

A human action classifier from 4-D data (3-D+Time) - Based o...

引用

2nd International Conference on Signal Processing and Multimedia Applications

作者： Pierobon, Massimiliano Marcon, Marco Sarti, Augusto Tubaro, Stefano Politecn Milan Dipartimento Elettron & Informat Image & Sound Proc Grp Piazza Leonardo Vinci 332 I-20133 Milan Italy

ISBN: (纸本)9789898111135

Many human action definitions have been provided in the field of human computer interaction studies. These distinctions could be considered merely semantical as human actions are all carried out performing sequences of body postures. In this paper we propose a human action classifier based on volumetric reconstructed sequences (4-D data) acquired from a multi-viewpoint camera system. In order to design the most general action classifier possible, we concentrate our attention in extracting only posture-dependent information from volumetric frames and in performing action distinction only on the basis of the sequence of body postures carried out in the scene. An Invariant Shape Descriptor (ISD) is used in order to properly describe the body shape and its dynamic changes during an action execution. The ISD data is then analyzed in order to extract suitable features able to meaningfully represent a human action independently from body position, orientation, size and proportions. The action classification is performed using a supervised recognizer based on the Hidden Markov Models (HMM) theory. Experimental results, evaluated using an extensive action sequence dataset and applying different training conditions to the HMM-based classifier, confirm the reliability of the proposed approach.

关键词： action recognition action classification gesture recognition gesture classification human motion analysis video surveillance human machine interaction computer vision multiple view volumetric reconstruction voxel based representation of human body 3D shape description principal component analysis pattern recognition context-dependent recognition Hidden Markov models

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Analysis of kernel distortion-invariant filters

Analysis of kernel distortion-invariant filters

引用

Conference on Intelligent Robots and computer vision XXV - Algorithms, Techniques, and Active vision

作者： Casasent, David Patnaik, Rohit Carnegie Mellon Univ Dept ECE Pittsburgh PA 15213 USA

ISBN: (纸本)9780819469243

Kernel techniques have been used in support vector machines (SVMs), feature spaces, etc. In kernel methods, the well-known kernel trick is used to implicitly map the input data to a higher-dimensional feature space. If all terms can be written as a kernel function, one can then use data in higher-dimensional space without actually computing the higher-dimensional features or knowing the mapping function (D. In this paper, we address kernel distortion-invariant filters (DIFs). Standard DIFs are synthesized in a linear feature space (in the image or Fourier domain). They are fast since they use FFT-based correlations. If the data is mapped to a higher-dimensional feature space before filter synthesis and before performing correlations, kernel filters result and performance can be improved. Kernel versions of several DIFs (OTF, SDF, and Mace) have been presented in prior work. However, several key issues were ignored in all prior work. These include : the unrealistic assumption of centered data in tests, the significantly larger storage and on-line computation time required, and the proper type of energy minimization in filter synthesis to reduce false peaks is necessary when the filters are applied to target scenes and has yet to be done. In addition, prior kernel DIF work used test set data to select the value of the kernel parameter. In this paper, we analyze these issues, present supporting test results on two face databases, and present several improvements to prior kernel DIF work.

关键词： composite filter correlation filter distortion-invariant filter kernel filter kernel methods pattern recognition

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Quality controlled multimodal fusion of biometrie experts

Quality controlled multimodal fusion of biometrie experts

引用

12th Iberoamerican Congress on pattern recognition, CIARP 2007

作者： Fatukasi, Omolara Kittler, Josef Poh, Norman Centre for Vision Speech and Signal Processing University of Surrey Guildford GU2 7XH Surrey United Kingdom

ISBN: (纸本)9783540767244

The quality of biometric samples used by multimodal biometric experts to produce matching scores has a significant impact on their fusion. We address the problem of quality controlled fusion of multiple biometric experts and focus on the fusion problem in a scenario where biometric trait quality expressed in terms of quality measures can be coarsely quantised. We develop a fusion methodology based on fixed rules that exploit the respective advantages of the sum and product rules and can be easily trained. We show in experimental studies on the XM2VTS database that the proposed method is very promising. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Biometrics

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Recognizing Groceries in situ Using in vitro Training Data

Recognizing Groceries in situ Using in vitro Training Data

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Michele Merler Carolina Galleguillos Serge Belongie Telecommunications Engineering University of Trento Italy Computer Science & Engineering University of California San Diego USA

The problem of using pictures of objects captured under ideal imaging conditions (here referred to as in vitro) to recognize objects in natural environments (in situ) is an emerging area of interest in computer vision and pattern recognition. Examples of tasks in this vein include assistive vision systems for the blind and object recognition for mobile robots; the proliferation of image databases on the web is bound to lead to more examples in the near future. Despite its importance, there is still a need for a freely available database to facilitate study of this kind of training/testing dichotomy. In this work one of our contributions is a new multimedia database of 120 grocery products, GroZi-120. For every product, two different recordings are available: in vitro images extracted from the web, and in situ images extracted from camcorder video collected inside a grocery store. As an additional contribution, we present the results of applying three commonly used object recognition/detection algorithms (color histogram matching, SIFT matching, and boosted Haar-like features) to the dataset. Finally, we analyze the successes and failures of these algorithms against product type and imaging conditions, both in terms of recognition rate and localization accuracy, in order to suggest ways forward for further research in this domain.

关键词： In vitro Training data pattern recognition Image recognition Object recognition Image databases computer vision Veins Machine vision Mobile robots

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