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检索条件"任意字段=IEEE-Computer-Society Conference on Computer Vision and Pattern Recognition Workshops"

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A visual vocabulary for flower classification

A visual vocabulary for flower classification

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Nilsback, Maria-Elena Zisserman, Andrew Robotics Research Group Department of Engineering Science University of Oxford United Kingdom

ISBN: (纸本)0769525970

We investigate to what extent 'bag of visual words' models can be used to distinguish categories which have significant visual similarity. To this end we develop and optimize a nearest neighbour classifier architecture, which is evaluated on a very challenging database of flower images. The flower categories are chosen to be indistinguishable on colour alone (for example), and have considerable variation in shape, scale, and viewpoint. We demonstrate that by developing a visual vocabulary that explicitly represents the various aspects (colour, shape, and texture) that distinguish one flower from another, we can overcome the ambiguities that exist between flower categories. The novelty lies in the vocabulary used for each aspect, and how these vocabularies are combined into a final classifier. The various stages of the classifier (vocabulary selection and combination) are each optimized on a validation set. Results are presented on a dataset of 1360 images consisting of 17 flower species. It is shown that excellent performance can be achieved, far surpassing standard baseline algorithms using (for example) colour cues alone. © 2006 ieee.

关键词： pattern recognition

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Human-focused computer vision applications

Human-focused computer vision applications

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International conference on computer Graphics, Imaging and Visualisation, CGIV'06

作者： Piccardi, Massimo Department of Computer Systems Faculty of IT University of Technology Sydney Australia UTS Computer Vision Research Group IEEE IEEE Computer Society International Association for Pattern Recognition

ISBN: (纸本)0769526063

Recent years have seen an increasing number of computer vision applications focusing on humans as their objects of interest. Such applications include video surveillance, domotics, multimedia semantic annotation and indexing, human-computer interfaces, affective computing, just to cite a few. What exactly are their "objects of interest"? A broad range of human-related features: motion, gestures, actions, interactions, activities, attitudes, behaviours, identity. This keynote will offer a survey of this field and present some current work from the speaker and his collaborators in the areas of emotion recognition and people tracking within camera networks. © 2006 ieee.

关键词： computer vision

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Real-time visual SLAM with resilience to erratic motion

Real-time visual SLAM with resilience to erratic motion

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Pupilli, Mark Calway, Andrew Department of Computer Science University of Bristol United Kingdom

ISBN: (纸本)0769525970

Simultaneous localisation and mapping using a single camera becomes difficult when erratic motions violate predictive motion models. This problem needs to be addressed when visual SLAM algorithms are transferred from robots or mobile vehicles onto hand-held or wearable devices. In this paper we describe a novel SLAM extension to a camera localisation algorithm based on particle filtering which provides resilience to erratic motion. The mapping component is based on auxiliary unscented Kalman filters coupled to the main particle filter via measurement covariances. This coupling allows the system to survive unpredictable motions such as camera shake, and enables a return to full SLAM operation once normal motion resumes. We present results demonstrating the effectiveness of the approach when operating within a desktop environment. © 2006 ieee.

关键词： Motion estimation

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An intensity-augmented ordinal measure for visual correspondence

An intensity-augmented ordinal measure for visual correspond...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Mittal, Anurag Ramesh, Visvanathan Real Time Vision and Modeling Siemens Corporate Research Princeton NJ 08540 Department of Computer Science and Engg. Indian Institute of Technology Madras Chennai- 600036 India

ISBN: (纸本)0769525970

Determining the correspondence of image patches is one of the most important problems in computer vision. When the intensity space is variant due to several factors such as the camera gain or gamma correction, one needs methods that are robust to such transformations. While the most common assumption is that of a linear transformation, a more general assumption is that the change is monotonic. Therefore, methods have been developed previously that work on the rankings between different pixels as opposed to the intensities themselves. In this paper, we develop a new matching method that improves upon existing methods by using a combination of intensity and rank information. The method considers the difference in the intensities of the changed pixels in order to achieve greater robustness to Gaussian noise. Furthermore, only uncorrelated order changes are considered, which makes the method robust to changes in a single or a few pixels. These properties make the algorithm quite robust to different types of noise and other artifacts such as camera shake or image compression. Experiments illustrate the potential of the approach in several different applications such as change detection and feature matching. © 2006 ieee.

关键词： Image analysis

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A refractive camera for acquiring stereo and super-resolution images

A refractive camera for acquiring stereo and super-resolutio...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Chunyu, Gao Ahuja, Narendra Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign

ISBN: (纸本)0769525970

We propose a novel depth sensing system composed of a single camera, and a transparent plate which is placed in front of the camera and rotates about the optical axis of the camera. The camera takes a sequence of images as the plate rotates, which provide the equivalent of a large number of stereo pairs. Compared with conventional multi-camera stereo systems, the use of a single camera for capturing stereo pairs helps improve the accuracy of detecting correspondences. The availability of the large number of stereo pairs also reduces matching ambiguities, even for objects with low texture. By using both the images and the estimated depth map, we show that the proposed system is also capable of generating super-resolution images. Experimental results on reconstructing 3D structures and recovering high-resolution images are presented. © 2006 ieee.

关键词： Cameras

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A joint illumination and shape model for visual tracking

A joint illumination and shape model for visual tracking

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Kale, Amit Jaynes, Christopher Ctr. for Visualization and Virtual Environments Department of Computer Science University of Kentucky

ISBN: (纸本)0769525970

Visual tracking involves generating an inference about the motion of an object from measured image locations in a video sequence. In this paper we present a unified framework that incorporates shape and illumination in the context of visual tracking. The contribution of the work is twofold. First, we introduce a a multiplicative, low dimensional model of illumination that is defined by a linear combination of a set of smoothly changing basis functions. Secondly, we show that a small number of centroids in this new space can be used to represent the illumination conditions existing in the scene. These centroids can be learned from ground truth and are shown to generalize well to other objects of the same class for the scene. Finally we show how this illumination model can be combined with shape in a probabilistic sampling framework. Results of the joint shape-illumination model are demonstrated in the context of vehicle and face tracking in challenging conditions. © 2006 ieee.

关键词： Tracking (position)

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Hierarchical statistical learning of generic parts of object structure

Hierarchical statistical learning of generic parts of object...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Fidler, Sanja Berginc, Gregor Leonardis, Aleš Faculty of Computer and Information Science University of Ljubljana Slovenia

ISBN: (纸本)0769525970

With the growing interest in object categorization various methods have emerged that perform well in this challenging task, yet are inherently limited to only a moderate number of object classes. In pursuit of a more general categorization system this paper proposes a way to overcome the computational complexity encompassing the enormous number of different object categories by exploiting the statistical properties of the highly structured visual world. Our approach proposes a hierarchical acquisition of generic parts of object structure, varying from simple to more complex ones, which stem from the favorable statistics of natural images. The parts recovered in the individual layers of the hierarchy can be used in a top-down manner resulting in a robust statistical engine that could be efficiently used within many of the current categorization systems. The proposed approach has been applied to large image datasets yielding important statistical insights into the generic parts of object structure. © 2006 ieee.

关键词： Learning systems

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Ultrasound-specific segmentation via decorrelation and statistical region-based active contours

Ultrasound-specific segmentation via decorrelation and stati...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Slabaugh, Greg Unal, Gozde Tong, Fang Wels, Michael Intelligent Vision and Reasoning Department Siemens Corporate Research Princeton NJ United States Department of Computer Science Universität Würzburg Coburg Germany

ISBN: (纸本)0769525970

Segmentation of ultrasound images is often a very challenging task due to speckle noise that contaminates the image. It is well known that speckle noise exhibits an asymmetric distribution as well as significant spatial correlation. Since these attributes can be difficult to model, many previous ultrasound segmentation methods oversimplify the problem by assuming that the noise is white and/or Gaussian, resulting in generic approaches that are actually more suitable to MR and X-ray segmentation than ultrasound. Unlike these methods, in this paper we present an ultrasound-specific segmentation approach that first decorrelates the image, and then performs segmentation on the whitened result using statistical region-based active contours. In particular, we design a gradient ascent flow that evolves the active contours to maximize a log likelihood functional based on the Fisher-Tippett distribution. We present experimental results that demonstrate the effectiveness of our method. © 2006 ieee.

关键词： Image segmentation

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Aligning ASL for statistical translation using a discriminative word model

Aligning ASL for statistical translation using a discriminat...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Farhadi, Ali Forsyth, David Computer Science Department University of Illinois Urbana-Champaign

ISBN: (纸本)0769525970

We describe a method to align ASL video subtitles with a closed-caption transcript. Our alignments are partial, based on spotting words within the video sequence, which consists of joined (rather than isolated) signs with unknown word boundaries. We start with windows known to contain an example of a word, but not limited to it. We estimate the start and end of the word in these examples using a voting method. This provides a small number of training examples (typically three per word). Since there is no shared structure, we use a discriminative rather than a generative word model. While our word spotters are not perfect, they are sufficient to establish an alignment. We demonstrate that quite small numbers of good word spotters results in an alignment good enough to produce simple English-ASL translations, both by phrase matching and using word substitution. © 2006 ieee.

关键词： Translation (languages)

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Seamless image stitching of scenes with large motions and exposure differences

Seamless image stitching of scenes with large motions and ex...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Eden, Ashley Uyttendaele, Matthew Szeliski, Richard Computer Science Division U.C. Berkeley Interactive Visual Media Group Microsoft Research

ISBN: (纸本)0769525970

This paper presents a technique to automatically stitch multiple images at varying orientations and exposures to create a composite panorama that preserves the angular extent and dynamic range of the inputs. The main contribution of our method is that it allows for large exposure differences, large scene motion or other misregistrations between frames and requires no extra camera hardware. To do this, we introduce a two-step graph cut approach. The purpose of the first step is to fix the positions of moving objects in the scene. In the second step, we fill in the entire available dynamic range. We introduce data costs that encourage consistency and higher signal-to-noise ratios, and seam costs that encourage smooth transitions. Our method is simple to implement and effective. We demonstrate the effectiveness of our approach on several input sets with varying exposures and camera orientations. © 2006 ieee.

关键词： Image analysis

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