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Multi-primitive hierarchical (MPH) stereo system

Multi-primitive hierarchical (MPH) stereo system

引用

conference on computer vision and pattern recognition (CVPR)

作者： S.B. Marapane M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA

A computational framework for an accurate, robust, and efficient stereo approach is developed. Most of the deficiencies prevailing in current computational models of stereo can be attributed to their use of a single, typically edge-element-based, primitive for stereo analysis and to their use of a single-level control strategy. The multi-primitive hierarchical (MPH) framework for stereo analysis presented is directed toward overcoming these deficiencies. In the MPH model, stereo analysis is performed in multiple stages, incorporating multiple primitives and utilizing a hierarchical control strategy. The higher levels of the hierarchical system are based on primitives containing more semantic information, and the results of stereo analysis at higher levels are used for guidance at the lower levels. It is shown that such a stereo system is superior to a single-level, single-primitive system.< >

关键词： Stereo vision computer vision Laboratories Robustness Computational modeling Performance analysis Layout Contracts Algorithm design and analysis Robot vision systems

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Gender classification from hand shape

Gender classification from hand shape

引用

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

作者： Gholamreza Amayeh George Bebis Mircea Nicolescu Computer Vision Laboratory University of Nevada Reno NV USA

Many social interactions and services today depend on gender. In this paper, we investigate the problem of gender classification from hand shape. Our work has been motivated by studies in anthropometry and psychology suggesting that it is possible to distinguish between male and female hands by considering certain geometric features. Our system segments the hand silhouette into six different parts corresponding to the palm and fingers. To represent the geometry of each part, we use region and boundary features based on Zernike moments and Fourier descriptors. For classification, we compute the distance of a given part from two different eigenspaces, one corresponding to the male class and the other corresponding to female class. We have experimented using each part of the hand separately as well as fusing information from different parts of the hand. Using a small database containing 20 males and 20 females, we report classification results close to 98% using score-level fusion and LDA.

关键词： Shape Fingers Humans Face detection computer vision Psychology Data mining Robustness Laboratories Anthropometry

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Attention estimation by simultaneous observation of viewer and view

Attention estimation by simultaneous observation of viewer a...

引用

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

作者： Anup Doshi Mohan M. Trivedi Computer Vision and Robotics Research Lab University of California San Diego La Jolla CA USA

We introduce a new approach to analyzing the attentive state of a human subject, given cameras focused on the subject and their environment. In particular, the task of analyzing the focus of attention of a human driver is of primary concern. Up to 80% of automobile crashes are related to driver inattention; thus it is important for an Intelligent Driver Assistance System (IDAS) to be aware of the driver state. We present a new Bayesian paradigm for estimating human attention specifically addressing the problems arising in dynamic situations. The model incorporates vision-based gaze estimation, “top-down”- and “bottom-up”-based visual saliency maps, and cognitive considerations such as inhibition of return and center bias that affect the relationship between gaze and attention. Results demonstrate the validity on real driving data, showing quantitative improvements over systems using only gaze or only saliency, and elucidate the value of such a model for any human-machine interface.

关键词： Humans Layout State estimation Bayesian methods Vehicle dynamics Robot vision systems Man machine systems Probability distribution Computational modeling Observers

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High Level Activity recognition using Low Resolution Wearable vision

High Level Activity Recognition using Low Resolution Wearabl...

引用

ieee computer society conference on computer vision and pattern recognition Workshops

作者： Sudeep Sundaram Walterio W. Mayol Cuevas Department of Computer Science University of Bristol UK

ISBN: (纸本)9781424439942

This paper presents a system aimed to serve as the enabling platform for a wearable assistant. The method observes manipulations from a wearable camera and classifies activities from roughly stabilized low resolution images (160×120 pixels) with the help of a 3-level Dynamic Bayesian Network and adapted temporal templates. Our motivation is to explore robust but computationally inexpensive visual methods to perform as much activity inference as possible without resorting to more complex object or hand detectors. The description of the method and results obtained are presented, as well as the motivation for further work in the area of wearable visual sensing.

关键词： Cameras Wearable sensors Bayesian methods Manipulator dynamics Robustness Sensor arrays Image resolution Pixel Object detection Wearable computers

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Empirical filter estimation for subpixel interpolation and matching

Empirical filter estimation for subpixel interpolation and m...

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8th International conference on computer vision

作者： Triggs, B. CNRS-INRIA 655 Avenue De l'Europe 38330 Montbonnot France

We study the low-level problem of predicting pixel intensities after subpixel image translations. This is a basic subroutine for image warping and super-resolution, and it has a critical influence on the accuracy of subpixel matching by image correlation. Rather than using traditional frequency-space filtering theory or ad hoc interpolators such as splines, we take an empirical approach, finding optimal subpixel interpolation filters by direct numerical optimization over a large set of training examples. The training set is generated by sub-sampling larger images at different translations, using subsamplers that mimic the spatial response functions of real pixels. We argue that this gives realistic results, and design filters of various different parametric forms under traditional and robust prediction error metrics. We systematically study the performance of the resulting filters, paying particular attention to the influence of the underlying image sampling regime and the effects of aliasing ("jaggies"). We summarize the results and give practical advice for obtaining subpixel accuracy.

关键词： pattern matching

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Verifying model-based alignments in the presence of uncertainty

Verifying model-based alignments in the presence of uncertai...

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conference on computer vision and pattern recognition (CVPR)

作者： T.D. Alter W.E.L. Grimson Artificial Intelligence Laboratory MIT Cambridge MA USA

This paper introduces a unified approach to the problem of verifying alignment hypotheses in the presence of substantial amounts of uncertainty in the predicted locations of projected model features. Our approach is independent of whether the uncertainty is distributed or bounded, and, moreover, incorporates information about the domain in a formally correct manner. Information which can be incorporated includes the error model, the distribution of background features, and the positions of the data features near each predicted model feature. Experiments are described that demonstrate the improvement over previously used methods. Furthermore, our method is efficient in that the number of operations is on the order of the number of image features that lie nearby the predicted model features.

关键词： Uncertainty Predictive models Robustness Solid modeling Image recognition Testing Image analysis Artificial intelligence Laboratories computer vision

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A new closed-form solution for absolute orientation

A new closed-form solution for absolute orientation

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

作者： Zhengyan Wang Jepson Department of Computer Science University of Toronto Toronto Canada

Presents a closed-form solution for the determination of 3D displacement and rotation parameters, given a set of 3D point correspondences. The method applies to the general case of arbitrary displacement and rotation with respect to an arbitrary stationary scene. The approach is based on the linear subspace method, which allows separate linear equations to be extracted for the displacement and rotation. This leads to a simple algorithm, suitable for real-time implementations, for the determination of both the 3D transformation and error estimates for the estimated 3D displacement. Preliminary experimental results with range data are presented.< >

关键词： Machine vision Geometric modeling Real-time systems

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Image authentication by detecting traces of demosaicing

Image authentication by detecting traces of demosaicing

引用

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

作者： Andrew C. Gallagher Tsuhan Chen Carnegie Mellon University USA Eastman Kodak (Japan) Limited USA

With increasing technical advances, computer graphics are becoming more photorealistic. Therefore, it is important to develop methods for distinguishing between actual photographs from digital cameras and computer generated images. We describe a novel approach to this problem. Rather than focusing on the statistical differences between the image textures, we recognize that images from digital cameras contain traces of resampling as a result of using a color filter array with demosaicing algorithms. We recognize that estimation of the actual demosaicing parameters is not necessary; rather, detection of the presence of demosaicing is the key. The in-camera processing (rather than the image content) distinguishes the digital camera photographs from computer graphics. Our results show high reliability on a standard test set of JPEG compressed images from consumer digital cameras. Further, we show the application of these ideas for accurately localizing forged regions within digital camera images.

关键词： Authentication Digital cameras computer graphics Image generation Image texture Image recognition Digital filters Testing Transform coding Image coding

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Real-Time Semi-Automatic Segmentation Using a Bayesian Network

Real-Time Semi-Automatic Segmentation Using a Bayesian Netwo...

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conference on computer vision and pattern recognition (CVPR)

作者： E.N. Mortensen Jin Jia Oregon State University USA Microsoft

This paper presents a semi-automatic segmentation technique called Bayesian cut that formulates object boundary detection as the most probable explanation (MPE) of a Bayesian network’s joint probability distribution. A two-layer Bayesian network structure is formulated from a planar graph representing a watershed segmentation of an image. The network’s prior probabilities encode the confidence that an edge in the planar graph belongs to an object boundary while the conditional probability tables (CPTs) enforce global contour properties of closure and simplicity (i.e., no self-intersections). Evidence, in the form of one or more connected boundary points, allows the network to compute the MPE with minimal user guidance. The constraints imposed by CPTs also permit a linear-time algorithm to compute the MPE, which in turn allows for interactive segmentation where every mouse movement recomputes the MPE based on the current cursor position and displays the corresponding segmentation.

关键词： Bayesian methods Image segmentation Markov random fields Feedback Displays computer networks Graphical models computer society computer vision pattern recognition

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S-AdaBoost and pattern detection in complex environment

S-AdaBoost and pattern detection in complex environment

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conference on computer vision and pattern recognition (CVPR)

作者： J.L. Jiang Kia-Fock Loe School of Computing National University of Singapore Singapore Singapore

S-AdaBoost is a new variant of AdaBoost and is more effective than the conventional AdaBoost in handling outliers in pattern detection and classification in real world complex environment. Utilizing the divide and conquer principle, S-AdaBoost divides the input space into a few sub-spaces and uses dedicated classifiers to classify patterns in the sub-spaces. The final classification result is the combination of the outputs of the dedicated classifiers. S-AdaBoost system is made up of an AdaBoost divider, an AdaBoost classifier, a dedicated classifier for outliers, and a non-linear combiner. In addition to presenting face detection test results in a complex airport environment, we have also conducted experiments on a number of benchmark databases to test the algorithm. The experiment results clearly show S-AdaBoost's effectiveness in pattern detection and classification.

关键词： Face detection Airports Boosting pattern analysis Benchmark testing Polynomials Algorithm design and analysis pattern classification Image databases computer society

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