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A GPU-based algorithm for estimating 3D geometry and motion in near real-time

A GPU-based algorithm for estimating 3D geometry and motion ...

引用

3rd Canadian conference on computer and Robot vision, CRV 2006

作者： Gong, Minglun Department of Math and Computer Science Laurentian University Sudbury Ont. P3E 6K1 Canada

ISBN: (纸本)0769525423

Real-time 3D geometry and motion estimation has many important applications in areas such as robot navigation and dynamic image-based rendering. A novel algorithm is proposed in this paper for estimating 3D geometry and motion of dynamic scenes based on captured stereo sequences. All computations are conducted in the 2D image space of the center view and the results are represented in forms of disparity maps and disparity flow maps. A dynamic programming based technique is used for searching global optimal disparity maps and disparity flow maps under an energy minimization framework. To achieve high processing speed, most operations are implemented on the Graphics Processing Units (GPU) of programmable graphics hardware. As a result, the derived algorithm is capable of producing both 3D geometry and motion information for dynamic scenes in near real-time. Experiments on two trinocular stereo sequences demonstrate that the proposed algorithm can handle scenes that contain non-rigid motion as well as those captured by moving cameras. © 2006 ieee.

关键词： Motion estimation

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Multi-Scale Contour Extraction Based on Natural Image Statistics

Multi-Scale Contour Extraction Based on Natural Image Statis...

引用

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

作者： F.J. Estrada J.H. Elder Centre for Vision Research York University Toronto ONT Canada

Perceptual grouping of the complete boundaries of objects in natural images remains an unsolved problem in computer vision. The computational complexity of the problem and difficulties capturing global constraints limit the performance of current algorithms. In this paper we develop a coarse-to-fine Bayesian algorithm which addresses these constraints. Candidate contours are extracted at a coarse scale and then used to generate spatial priors on the location of possible contours at finer scales. In this way, a rough estimate of the shape of an object is progressively refined. The coarse estimate provides robustness to texture and clutter while the refinement process allows for the extraction of detailed object contours. The grouping algorithm is probabilistic and uses multiple grouping cues derived from natural scene statistics. We present a quantitative evaluation of grouping performance on the Berkeley Segmentation Database, and show that the multi-scale approach outperforms several single-scale contour extraction algorithms.

关键词： Statistics Shape Layout computer vision Image segmentation Image databases Computational complexity Bayesian methods Robustness Data mining

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Automated detection of unusual events on stairs

Automated detection of unusual events on stairs

引用

3rd Canadian conference on computer and Robot vision, CRV 2006

作者： Snoek, Jasper Hoey, Jesse Stewart, Liam Zemel, Richard S. Department of Computer Science University of Toronto 10 King's College Rd. Toronto Ont. Canada

ISBN: (纸本)0769525423

This paper presents a method for automatically detecting and recognising unusual events on stairs from video data. The motivation is to provide a tool for biomedical researchers to rapidly find and analyse the events of interest within large quantities of video data. Our system identifies potential sequences containing anomalies, and reduces the amount of data that needs to be searched by a human. We apply adaptive background subtraction to segment the person using the stairs, followed by affine flow computation over the segmented region. A hidden Markov model (HMM) is then used to analyse the temporal progression of the affine features. A single HMM is trained on sequences of normal stair use, and a threshold is used to detect unusual events in new data. We also introduce a temporal segmentation method using a conditional random field (CRF). We demonstrate our system on a data set with three persons. © 2006 ieee.

关键词： Video signal processing

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Finding Minimal Parameterizations of Cylindrical Image Manifolds

Finding Minimal Parameterizations of Cylindrical Image Manif...

引用

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

作者： M. Dixon N. Jacobs R. Pless Department of Computer Science and Engineering Washington University Saint Louis MO USA

Manifold learning has become an important tool to characterize high-dimensional data that vary nonlinearly due to a few parameters. Applications to the analysis of medical imagery and human motion patterns have been successful despite the lack of effective tools to parameterize cyclic data sets. This paper offers an initial approach to this problem, and provides for a minimal parameterization of points that are drawn from cylindrical manifolds-data whose (unknown) generative model includes a cyclic and a non-cyclic parameter. Solving for this special case is important for a number of current, practical applications and provides a start toward a general approach to cyclic manifolds. We offer results on synthetic and real data sets and illustrate an application to de-noising cardiac ultrasound images.

关键词： Topology Manifolds Jacobian matrices Noise reduction Ultrasonic imaging computer science Biomedical engineering Data engineering Application software Image analysis

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Beyond RANSAC: User Independent Robust Regression

Beyond RANSAC: User Independent Robust Regression

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

作者： R. Subbarao P. Meer Department of Electrical and Computer Engineering Rutgers University Piscataway NJ USA

RANSAC is the most widely used robust regression algorithm in computer vision. However, RANSAC has a few drawbacks which make it difficult to use in a lot of applications. Some of these problems have been addressed through improved sampling algorithms or better cost functions, but an important problem still remains. The algorithms are not user independent, and require some knowledge of the scale of the inlier noise. The projection based M-estimator (pbM) offers a solution to this by reframing the regression problem in a projection pursuit framework. In this paper we derive the pbM algorithm for heteroscedastic data. Our algorithm is applied to various real problems and its performance is compared with RANSAC and MSAC. It is shown that pbM gives better results than RANSAC and MSAC in spite of being user independent.

关键词： computer vision Application software Sampling methods Motion estimation Parameter estimation Cost function Interference Noise robustness Project management Kernel

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Gabor Filter Analysis for Texture Segmentation

Gabor Filter Analysis for Texture Segmentation

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

作者： R. Sandler M. Lindenbaum Computer Science Department Technion-Israel Institute of Technology Haifa Israel

Gabor features are a common choice for texture analysis. The particular set of Gabor filters used for extracting the features is usually designed for optimal signal representation. We propose here an alternative criterion for designing the filter set. We consider a set of filters and its response to pairs of harmonic signals. Two signals are considered separable if the corresponding two sets of vector responses are disjoint in at least one of the components. We look for the set of Gabor filters that maximizes the fraction of separable harmonic signal pairs. The resulting filters are significantly different from the traditional ones. We test these maximal harmonic discrimination (MHD) filters using two texture discrimination methods, and describe their advantages over traditional filters.

关键词： Gabor filters Power harmonic filters Image segmentation Signal design Distortion measurement Signal analysis Stability Harmonic analysis computer science Feature extraction

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Discriminative Patch Selection using Combinatorial and Statistical Models for Patch-Based Object recognition

Discriminative Patch Selection using Combinatorial and Stati...

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

作者： A. Vashist Zhipeng Zhao A. Elgammal I. Muchnik C. Kulikowski Department of Computer Science State University of New Jersey Rutgers Piscataway NJ USA

In an object recognition task where an image is represented as a constellation of image patches, often many patches correspond to the cluttered background. If such patches are used for object class recognition, they will adversely affect the recognition rate. In this paper, we present a two stage method for selecting image patches which characterize the target object class and are capable of discriminating between the positive images containing the target objects and the complementary negative images. The first stage selection is done using a novel combinatorial optimization formulation on a weighted multipartite graph representing similarities between images patches across different instances of the target object. The following stage is a statistical method for selecting those images patches from the positive images which, when used individually, have the power of discriminating between the positive and negative images in the evaluation data. The individual methods have a performance competitive with the state of the art methods on a popular benchmark data set and their sequential combination consistently outperforms the individual methods and most of the other known methods while approaching the best known results.

关键词： Object recognition Solid modeling Feature extraction Object detection computer vision Image recognition Face detection pattern recognition computer science Statistical analysis

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Moving Object Localization in Thermal Imagery by Forward-backward MHI

Moving Object Localization in Thermal Imagery by Forward-bac...

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

作者： Zhaozheng Yin R. Collins Department of Computer Science and Engineering Pennsylvania State University University Park PA USA

Detecting moving objects automatically is a key component of an automatic visual surveillance and tracking system. In airborne thermal video, the moving objects may be small, color information is not available, and even intensity appearance may be camouflaged. Previous motionbased moving object detection approaches often use background subtraction, inter-frame difference or three-frame difference. In this paper, we describe a detection and localization method based on forward-backward motion history images (MHI). This method can accurately detect location and shape of moving objects for initializing a tracker. Using long and varied video sequences, we quantify the effectiveness of this method.

关键词： Object detection Shape Motion detection Cameras Surveillance Image reconstruction Thermal engineering computer science History Video sequences

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Good Continuation in Layers: Shading flows, color flows, surfaces and shadows

Good Continuation in Layers: Shading flows, color flows, sur...

引用

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

作者： O. Ben-Shahar A. Glaser S.W. Zucker Computer Science Ben-Gurion University of the Negev Israel Applied Mathematics Yale University New Heaven CT USA Computer Science Yale University New Heaven CT USA

We extend the concept of good continuation in a uniform fashion from boundaries to shading, hue, and texture. Each has the property that local measurements yield an orientation, which we explicitly establish for hue using geometric harmonic techniques. Good continuation arises in a geometric sense, because these orientations all vary smoothly in an appropriate sense. Thus they correspond to flows. Taken together they define a layered set of flows, in the sense the "horizontal" computations within each flow provide global consistency while "vertical" computations across flows enable the identification of shading and shadowing and different types of edges. Evidence is reviewed that primate visual systems enjoy such an organization.

关键词： computer science Computed tomography Shadow mapping Visual system computer vision Surface texture Mathematics Color Image segmentation Light sources

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Empirical Studies of the Existence of the Biometric Menagerie in the FRGC 2.0 Color Image Corpus

Empirical Studies of the Existence of the Biometric Menageri...

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

作者： M. Wittman P. Davis P.J. Flynn Department of Computer Science and Engineering University of Notre Dame Notre Dame IN USA

The issue of recognizability of subjects in biometric identification is of particular interest to the designers of these systems. We have applied the concept of Doddington’s biometric menagerie to the area of facial recognition. We performed a series of tests for the presence of goats, lambs, and wolves on FRGC 2.0 color image data. The data for the subjects that appeared at the extreme end of these tests was then visually examined. Even a cursory comparison of images showed that for this set of data, some images fell into the defined menagerie categories. Our tests show the statistical existence of these animal classifications within the constraints of this set of FRGC 2.0 data using the baseline matching algorithm. Ultimately, these tests were limited by the image data set and matching algorithm used. For further confirmation of the existence of the menagerie, the analysis must be expanded to include different image sets and matching algorithms..

关键词： Biometrics Color Testing Face recognition Probes Principal component analysis Image analysis Statistics computer science USA Councils

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