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Region Classification with Markov Field Aspect Models

Region Classification with Markov Field Aspect Models

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Jakob Verbeek Bill Triggs LJK INRIA Montbonnot France

Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-of-feature approaches label each pixel or patch independently. More advanced models attempt to improve the coherence of the labellings by introducing some form of inter-patch coupling: traditional spatial models such as MRF's provide crisper local labellings by exploiting neighbourhood-level couplings, while aspect models such as PLSA and LDA use global relevance estimates (global mixing proportions for the classes appearing in the image) to shape the local choices. We point out that the two approaches are complementary, combining them to produce aspect-based spatial field models that outperform both approaches. We study two spatial models: one based on averaging over forests of minimal spanning trees linking neighboring image regions, the other on an efficient chain-based Expectation Propagation method for regular 8-neighbor Markov random fields. The models can be trained using either patch-level labels or image-level keywords. As input features they use factored observation models combining texture, color and position cues. Experimental results on the MSR Cambridge data sets show that combining spatial and aspect models significantly improves the region-level classification accuracy. In fact our models trained with image-level labels outperform PLSA trained with pixel-level ones.

关键词： Labeling Image segmentation Pixel Linear discriminant analysis Animals Coherence Joining processes Markov random fields computer vision Layout

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On Constant Focal Length Self-Calibration From Multiple Views

On Constant Focal Length Self-Calibration From Multiple View...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Benoit Bocquillon Adrien Bartoli Pierre Gurdjos Alain Crouzil UPS-IRIT France CNRS-LASMEA France

We investigate the problem of finding the metric structure of a general 3D scene viewed by a moving camera with square pixels and constant unknown focal length. While the problem has a concise and well-understood formulation in the stratified framework thanks to the absolute dual quadric, two open issues remain. The first issue concerns the generic Critical Motion Sequences, i.e. camera motions for which self-calibration is ambiguous. Most of the previous work focuses on the varying focal length case. We provide a thorough study of the constant focal length case. The second issue is to solve the nonlinear set of equations in four unknowns arising from the dual quadric formulation. Most of the previous work either does local nonlinear optimization, thereby requiring an initial solution, or linearizes the problem, which introduces artificial degeneracies, most of which likely to arise in practice. We use interval analysis to solve this problem. The resulting algorithm is guaranteed to find the solution and is not subject to artificial degeneracies. Directly using interval analysis usually results in computationally expensive algorithms. We propose a carefully chosen set of inclusion functions, making it possible to find the solution within few seconds. Comparisons of the proposed algorithm with existing ones are reported for simulated and real data.

关键词： Cameras Collision mitigation Image reconstruction Layout Nonlinear equations Algorithm design and analysis Computational modeling computer vision Surface reconstruction Uninterruptible power systems

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Simultaneous Optimization of Structure and Motion in Dynamic Scenes Using Unsynchronized Stereo Cameras

Simultaneous Optimization of Structure and Motion in Dynamic...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Akihito Seki Masatoshi Okutomi Graduate School of Science and Engineering Tokyo Institute of Technology Tokyo Japan

In this paper, we propose a simultaneous estimation method of structure and motion in dynamic scenes. Usual methods for obtaining structure and motion using stereo cameras require two kinds of operations: stereo correspondence and tracking. Therefore, we must separately determine the correspondence between stereo images and sequential images. This necessity complicates the algorithm and increases the possibility of mismatches because of the object's motion and visibility change in the images. Our proposed method makes two contributions. The first contribution is the method of corresponding all stereo images and sequential images at once. Therefore, we can obtain the structure and motion simultaneously and more accurately. On the other hand, most stereo correspondence algorithms are limited to use under a synchronized status. In a stereo rig using unsynchronized cameras, as are most commercially available cameras, the structure cannot be obtained by stereo correspondence and triangulation because of the unknown time offset between cameras. Therefore, our second contribution is a method of estimating structure, motion, and time offset simultaneously using unsynchronized stereo cameras. This latter task is accomplished by taking advantage of the first contribution scheme. Additionally, our method requires no preprocessing such as motion segmentation for separating identical-motion objects and advance calibration of the time offset. Finally, we present the experimental results using both synthetic and real images.

关键词： Layout Cameras Motion estimation Tracking Frequency synchronization Motion segmentation computer vision Timing Image motion analysis Image generation

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Visual detection, recognition, and classification of surface-buried UXO based on soft-computing decision fusion

Visual detection, recognition, and classification of surface...

引用

Conference on Detection and Remediation Technologies for Mines and Minelike Targets XII

作者： Shirkhodaie, Amir Rababaah, Haroun Tennessee State Univ Intelligent Tact Mobil Robot Res Lab Dept Mech & Mfg Engn 3500 John Merritt Blvd Nashville TN 37209 USA

ISBN: (纸本)9780819466754

In this paper, we have addressed the problem of visual inspection, recognition, and discrimination of UXO based on computer vision techniques and introduced three complimentary color, texture, and shape classifiers. The proposed technique initially enhances an image taken from an UXO site and removes terrain background. Next, it applies a blob detector to detect the salient objects of the environment. The UXO classification begins with a perceptive color classifier that classifies the found salient objects based on their color hues. The color classifier attempts to differentiate and classify the color of salient objects based on the color hue information of some known UXO objects in the database. A color ranking scheme is applied for ranking color hue likelihood of the salient objects in the environment. Next, an intuitive texture classifier is applied to characterize the surface texture of the salient objects. The texture signature is used to disjointedly discriminate objects whose surface texture properties matching the priori known UXO textures. Lasting, an intuitive Object Shape Classifier is applied to independently arbitrate the classification of the UXO. Three soft computing methods were developed for robust decision fusion of three UXO feature classifiers. These soft computing techniques include: a statistical-based genetic algorithm, a hamming neural network, and a fuzzy logic algorithm. In this paper, we present details of the UXO feature classifiers and discuss the performance of three decision fusion methods for fusion of results from the three UXO feature classifiers. The main contributing factor of this work is toward designing an ultimate fully-automated tele-robotic system for UXO classification and decontamination.

关键词： Unexploded Ordnance (UXO) soft computing pattern recognition shape-based classifier color-based classifier texture-based classifier data fusion

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Hand Gesture recognition Using Fast Multi-scale Analysis

Hand Gesture Recognition Using Fast Multi-scale Analysis

引用

International Conference on Image and Graphics (ICIG)

作者： Yikai Fang Jian Cheng Kongqiao Wang Hanqing Lu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China Nokia Research Center Beijing China

Hand gesture has been used as a natural and efficient way in human computer interaction. Due to independence of auxiliary input devices, vision-based hand interfaces is more favorable for users. However, the process of hand gesture recognition is very time consuming, which often brings much frustration to users. In this paper, we propose a fast feature detection and description approach which can significantly speed up hand gesture recognition. Firstly, integral image is used to approximate Gaussian derivatives to calculate image convolution in feature detection. Then multi-scale geometric descriptors at feature points are obtained to represent hand gestures. Finally gesture is recognized with its geometric configuration. Experiments show that the proposed method needs much less time consumption while obtains comparative performance with its counterpart in literatures.

关键词： computer vision Convolution Human computer interaction Detectors pattern recognition Pervasive computing Boosting Computational efficiency Pixel Graphics

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Hairline Fracture Detection using MRF and Gibbs Sampling

Hairline Fracture Detection using MRF and Gibbs Sampling

引用

IEEE Workshop on Applications of computer vision (WACV)

作者： A. S. Chowdhury A. Bhattacharya S. M. Bhandarkar G. S. Datta J. C. Yu R. Figueroa Department of Computer Science University of Georgia Athens GA USA Department of Statistics University of Georgia Athens GA USA Department of Plastic Surgery Medical College Augusta GA USA Department of Radiology Medical College Augusta GA USA

Detection of hairline fractures, representing points or areas of discontinuity in the bone, is a clinically challenging task, especially in presence of noise. The above problem is equally appealing from a computer vision or pattern recognition perspective since (a) traditional techniques for detection of corners, denoting points of surface discontinuity, typically fail in such cases and, (b) one needs to implicitly handle unknown local degradation in the image. A novel two-phase scheme for hairline mandibular fracture detection, that is robust to noise, is proposed. In the first phase, the hairline fractures are coarsely localized using statistical correlation and by exploiting the bilateral symmetry of the human mandible. In the second phase, the fractures are precisely identified and highlighted using a Markov random field (MRF) modeling approach coupled with maximum a posteriori probability (MAP) estimation. Gibbs sampling is used to maximize the posterior probability. Experimental results on computer tomography (CT) scans from real patients are presented

关键词： Sampling methods Probability Bones computer vision pattern recognition Surface cracks Degradation Noise robustness Humans Markov random fields

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Matching Relational Structures using the Edge-Association Graph

Matching Relational Structures using the Edge-Association Gr...

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International Conference on Image Analysis and Processing

作者： Andrea Torsello Andrea Albarelli Marcello Pelillo Dipartimento di Informatica Università Ca Foscari di Venezia Italy

The matching of relational structures is a problem that pervades computer vision and pattern recognition research. A classic approach is to reduce the matching problem into one of search of a maximum clique in an auxiliary structure: the association graph. The approach has been extended to incorporate vertex-attributes by reducing it to a weighted clique problem, but the extension to edge-attributed graphs has proven elusive. However, in vision problems, quite often the most relevant information is carried by edges. For example, when the graph abstracts scene layout, the edges can represent the relative position of the detected features, which abstracts the geometry of the scene in a way that is invariant to rotations and translations. In this paper, we provide a generalization of the association graph framework capable of dealing with attributes on both vertices and edges. Experiments are presented which demonstrate the effectiveness of the proposed approach.

关键词： Layout computer vision Abstracts Labeling Image edge detection pattern recognition pattern matching Geometry Gold Optimal matching

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Human body image segmentation based on wavelet analysis and active contour models

Human body image segmentation based on wavelet analysis and ...

引用

International Conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Jin-Yong Cheng Yi-Hui Liu School of Information Science and Technology Shandong Institute of Light Industry Jinan China

GVF Snake model is used widely in computer vision and image segmentation. However, there are problems in convergence processing to boundaries of human body image because of noise. This paper presents a new segmentation algorithm to human body image. First, rough edge is got by multi-scale algorithm of wavelet analysis, and then thinning method based on mathematical morphology is adopted to get edge map as foundation of GVF Snake model. This method solves the problem that the edge based on wavelets analysis is not consecutive. And it improves GVF Snake model's anti-noise ability. Experiments indicate that the new algorithm can improve snake model's ability to segment the complicated image.

关键词： Humans Image segmentation Wavelet analysis Image analysis Active contours Biological system modeling computer vision Convergence Algorithm design and analysis Morphology

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Combination of OCR Engines for Page Segmentation Based on Performance Evaluation

Combination of OCR Engines for Page Segmentation Based on Pe...

引用

International Conference on Document Analysis and recognition

作者： M. Ferrer E. Valveny Computer Vision Center-Department Ciències Computació Universitat Autònoma Barcelona Bellaterra Spain

ISBN: (纸本)9780769528229;0769528228

In this paper we present a method to improve the performance of individual page segmentation engines based on the combination of the output of several engines. The rules of combination are designed after analyzing the results of each individual method. This analysis is performed using a performance evaluation framework that aims at characterizing each method according to its strengths and weaknesses rather than computing a single performance measure telling which is the "best" segmentation method.

关键词： Optical character recognition software Engines Image segmentation computer vision Performance analysis Performance evaluation Particle measurements Text analysis pattern recognition

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PrivacyCam: a Privacy Preserving Camera Using uCLinux on the Blackfin DSP

PrivacyCam: a Privacy Preserving Camera Using uCLinux on the...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Ankur Chattopadhyay T.E. Boult Vision and Security Technology (VAST) Laboratory University of Colorado Colorado Springs Colorado Springs CO USA

Considerable research work has been done in the area of surveillance and biometrics, where the goals have always been high performance, robustness in security and cost optimization. With the emergence of more intelligent and complex video surveillance mechanisms, the issue of "privacy invasion" has been looming large. Very little investment or effort has gone into looking after this issue in an efficient and cost-effective way. The process of PICO (privacy through invertible cryptographic obscuration) is a way of using cryptographic techniques and combining them with image processing and video surveillance to provide a practical solution to the critical issue of "privacy invasion". This paper presents the idea and example of a realtime embedded application of the PICO technique, using uCLinux on the tiny Blackfin DSP architecture, along with a small Omnivision camera. It demonstrates how the practical problem of "privacy invasion" can be successfully addressed through DSP hardware in terms of smallness in size and cost optimization. After review of previous applications of "privacy protection", and system components, we discuss the "embedded jpeg-space" detection of regions of interest and the real time application of encryption techniques to improve privacy while allowing general surveillance to continue. The resulting approach permits full access (violation of privacy) only by access to the private-key to recover the decryption key, thereby striking a fine trade-off among privacy, security, cost and space.

关键词： Privacy Cameras Digital signal processing Cryptography Security Cost function Video surveillance Biometrics Robustness Investments

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