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检索条件"任意字段=2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006"

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An ontological service oriented and web searching mechanism in distributed e-learning repositories

An ontological service oriented and web searching mechanism ...

引用

6th International conference on Advanced Learning Technologies, ICALT 2006

作者： Votis, Konstantinos Alexakos, Christos Giotopoulos, Kostas Likothanassis, Spiridon Pattern Recognition Lab. Dept. of Computer Engineering and Informatics University of Patras Greece

ISBN: (纸本)0769526322

The great heterogeneity of web based Learning systems storing and providing digital e-learning data requires the introduction of interoperability aspects in order to resolve integration problems in a flexible and dynamic way. Learning Objects developed and stored in many different places on the web have a tremendous potential to benefit e-learning in particular and education in general. So the distributed e-learning data integration is significant for the enforcement of novel searching mechanisms in distributed e-learning repositories Our approach introduces an advanced search mechanism which initializes a semantic model representing the digital content stored in distributed e-learning servers, through the use of ontologies In order to retrieve useful content to be added to the learning environment while bypassing compatibility problems between different ontological representations of the same domain, we will use a mixed approach constituting both keywords and ontologies Searching tasks are carried out in the metadata level, where information concerning web digital content is published, managed and stored in the form of a scalable description of knowledge domains. © 2006 ieee.

关键词： Ontology

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Statistical Learning of Visual Feature Hierarchies

Statistical Learning of Visual Feature Hierarchies

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： F. Scalzo J.H. Piater University of Liège Liege Belgium

We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method combines these primitives into high-level abstractions. Our appearance-based learning method uses local statistical analysis between features and Expectation- Maximization (EM) to identify and code spatial correlations. Spatial correlation is asserted when two features tend to occur at the same relative position of each other. This learning scheme results in a graphical model that allows a probabilistic representation of a flexible visual feature hierarchy. For feature detection, evidence is propagated using Nonparametric Belief Propagation (NBP), a recent generalization of particle filtering. In experiments, the proposed approach demonstrates efficient learning and robust detection of object models in the presence of clutter and occlusion and under view point changes.

关键词： Statistical learning Graphical models computer vision Learning systems Belief propagation Application software Statistical analysis Filtering Robustness Object detection

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computer vision for music identification: video demonstration

Computer vision for music identification: video demonstratio...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Y. Ke D. Hoiem Rahul Sukthankar School of Computer Science Carnegie Mellon University Pittsburgh PA USA Intel Research Pittsburgh Pittsburgh PA USA

This paper describes a demonstration video for our music identification system. The goal of music identification is to reliably recognize a song from a small sample of noisy audio. This problem is challenging because the recording is often corrupted by noise and because the audio sample will only match a small portion of the target song. Additionally, a practical music identification system should scale (in both accuracy and speed) to databases containing hundreds of thousands of songs. Recently, the music identification problem has attracted considerable attention. However, the task remains unsolved, particularly for noisy real-world queries. We cast music identification into an equivalent sub-image retrieval framework: identify the portion of a spectrogram image from the database that best matches a given query snippet. Our approach treats the spectrogram of each music clip as a 2D image and transforms music identification into a corrupted sub-image retrieval problem.

关键词： computer vision Multiple signal classification Acoustic noise Spectrogram Music information retrieval Signal processing algorithms Audio recording Signal processing Speech analysis Image retrieval

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A slit scanning depth of route panorama from stationary blur

A slit scanning depth of route panorama from stationary blur

引用

conference on computer vision and pattern recognition (cvpr)

作者： Min Shi Jiang Yu Zheng Department of Computer Science Indiana University-Purdue University Indianapolis USA

ISBN: (纸本)0769523722

This work achieves an efficient acquisition of scenes and their depths along streets. During the movement of a vehicle, a slit in the camera frame is set properly to sample scenes continuously for a route panorama. This paper proposes a novel method of depth estimation by analyzing a new phenomenon named stationary blur in the route panorama. We find its relation with the depth and evaluate its degree at local and global levels. The depth estimation through filtering avoids feature matching and tracking that are error-prone in the scanning of real and complex street scenes. Our method provides reliable results but requires much less data than that of the structure from motion. This keeps the elegance of the route panorama in data representation, and is suitable for real time sensor development. Utilizing the completeness of the route panorama in the scene archiving, we can generate planar models of streets, which can be used in city visualization.

关键词： Layout Cameras Cities and towns Videos Vehicles Data visualization Image motion analysis pattern analysis computer science Matched filters

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A generative model of human hair for hair sketching

A generative model of human hair for hair sketching

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conference on computer vision and pattern recognition (cvpr)

作者： H. Chen S.C. Zhu Department of Statistics and Computer Science University of California Los Angeles USA

ISBN: (纸本)0769523722

Human hair is a very complex visual pattern whose representation is rarely studied in the vision literature despite its important role in human recognition. In this paper, we propose a generative model for hair representation and hair sketching, which is far more compact than the physically based models in graphics. We decompose a color hair image into three bands: a color band (a) (by Luv transform), a low frequency band (b) for lighting variations, and a high frequency band (c) for the hair pattern. Then we propose a three level generative model for the hair image (c). In this model, image (c) is generated by a vector field (d) that represents hair orientation, gradient strength, and directions; and this vector field is in turn generated by a hair sketch layer (e). We identify five types of primitives for the hair sketch each specifying the orientations of the vector field on the two sides of the sketch. With the five-layer representation (a-e) computed, we can reconstruct vivid hair images and generate hair sketches. We test our algorithm on a large data set of hairs and some results are reported in the experiments.

关键词： Hair Humans Graphics Image reconstruction pattern recognition Frequency Image generation Animation Image color analysis Statistics

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RGB-Z: mapping a sparse depth map to a high resolution RGB camera image

RGB-Z: mapping a sparse depth map to a high resolution RGB c...

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conference on computer vision and pattern recognition (cvpr)

作者： A. Rafii C. Rossbach P. Zhao Canesta Inc. USA

The video stream from a commercial RGB camera is mapped to a semi-synchronous video stream of a time-of-flight Z-depth camera to produce a composite RGB-Z video stream. The combined image is rendered to show both the color and depth effects of the scene. Each pixel of the composite image provides both RGB encoding and Z depth in real-world coordinates. The data is useful for both machine vision and consumer imaging applications. The RGB brightness data provides detailed image of the scene including textures, colors and ambient light information. The time-of-flight depth camera provides additional information about the relative location and size of objects independent of texture and ambient-light condition. The demo shows several 3D rendering technique including wire-frame and color shading.

关键词： Image resolution Cameras Streaming media Layout Pixel Brightness Rendering (computer graphics) Inference algorithms Signal resolution Infrared detectors

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Window-based, discontinuity preserving stereo

Window-based, discontinuity preserving stereo

引用

conference on computer vision and pattern recognition (cvpr)

作者： M. Agrawal L.S. Davis SRI International Inc. Menlo Park CA USA Department of Computer Science University of Maryland College Park MD USA

Traditionally, the problem of stereo matching has been addressed either by a local window-based approach or a dense pixel-based approach using global optimization. In this paper we present an algorithm which combines window-based local matching into a global optimization framework. Our local matching algorithm assumes that local windows can have at most two disparities. Under this assumption, the local matching can be performed very efficiently using graph cuts. The global matching is formulated as minimization of an energy term that takes into account the matching constraints induced by the local stereo algorithm. Fast, approximate minimization of this energy is achieved through graph cuts. The key feature of our algorithm is that it preserves discontinuities both during the local as well as global matching phase.

关键词： Stereo vision Layout computer vision Interpolation Iterative algorithms computer science Educational institutions Minimization methods Application software Light sources

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Word spotting: a new approach to indexing handwriting

Word spotting: a new approach to indexing handwriting

引用

conference on computer vision and pattern recognition (cvpr)

作者： R. Manmatha Chengfeng Han E.M. Riseman Dept. of Comput. Sci. Massachusetts Univ. Amherst MA USA Center for Intelligent Information Retrieval Computer Science Department University of Massachusetts Amherst MA USA

There are many historical manuscripts written in a single hand which it would be useful to index. Examples include the W.B. DuBois collection at the University of Massachusetts and the early Presidential libraries at the Library of Congress. Since Optical Character recognition (OCR) does not work well on handwriting, an alternative scheme based on matching the images of the words is proposed for indexing such texts. The current paper deals with the matching aspects of this process. Two different techniques for matching words are discussed. The first method matches words assuming that the transformation between the words may be modelled by a translation (shift). The second method matches words assuming that the transformation between the words may be modelled by an affine transform. Experiments are shown demonstrating the feasibility of the approach for indexing handwriting. The method should also be applicable to retrieving previously stored material from personal digital assistants (PDAs).

关键词： Indexing Optical character recognition software Handwriting recognition Personal digital assistants Software libraries Information retrieval computer science Image recognition Text recognition Information resources

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Model learning and recognition of nonrigid objects

Model learning and recognition of nonrigid objects

引用

conference on computer vision and pattern recognition (cvpr)

作者： J. Segen AT and T Bell Laboratories Holmdel NJ USA

A method of learning structural models of 2D shape from real data is described and demonstrated. These models can be used to classify nonrigid shapes, even if they are partially occluded, and to label their parts. The representation of a single shape is a layered graph whose vertices correspond to n-ary relations. A class of shapes is represented as a probability model whose outcome is a graph. The method is based on two types of learning: unsupervised learning used to discover relations, and supervised learning used to build class models. The class models are constructed incrementally, by matching and merging graphs representing shape instances. This process uses a fast graph-matching heuristic which seeks a simplest representation of a graph. An important feature is the self-generation of symbolic primitives by an unsupervised learning process. This feature makes it possible to apply the system to any set of shape data without adjustments, while other methods might require the user to provide a different set of primitives for each case.< >

关键词： Shape Biological system modeling Noise shaping Unsupervised learning Supervised learning Merging Humans Layout Character recognition

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Relative positioning from geometric invariants

Relative positioning from geometric invariants

引用

conference on computer vision and pattern recognition (cvpr)

作者： R. Mohr L. Morin LIFIA-IMAG Grenoble France

The author gives geometric constructive solutions for 3-D vision problems like positioning a point in space from two views. Using reference points in the scene, no calibration is needed. The method involves only simple geometric computation. From the experiments it is concluded that positioning 3-D points relatively to reference points, is easy and provides more reliable results than absolute positioning as is usually done.< >

关键词： Geometry Cameras Layout Calibration computer vision Robustness Transmission line matrix methods Data mining Information retrieval Motion estimation

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