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Non-Rigid Metric Shape and Motion Recovery from Uncalibrated Images Using Priors

Non-Rigid Metric Shape and Motion Recovery from Uncalibrated...

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Del Bue X. Llad L. Agapito Department of Computer Science University of London London UK

In this paper we focus on the estimation of the 3D Euclidean shape and motion of a non-rigid object which is moving rigidly while deforming and is observed by a perspective camera. Our method exploits the fact that it is often a reasonable assumption that some of the points are deforming throughout the sequence while others remain rigid. First we use an automatic segmentation algorithm to identify the set of rigid points which in turn is used to estimate the internal camera calibration parameters and the overall rigid motion. Finally we formalise the problem of non-rigid shape estimation as a constrained non-linear minimization adding priors on the degree of deformability of each point. We perform experiments on synthetic and real data which show firstly that even when using a minimal set of rigid points it is possible to obtain reliable metric information and secondly that the shape priors help to disambiguate the contribution to the image motion caused by the deformation and the perspective distortion.

关键词： Cameras Motion estimation Nonlinear distortion Shape measurement Noise shaping computer vision computer science Calibration Motion measurement Rotation measurement

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Stereo Matching with Symmetric Cost Functions

Stereo Matching with Symmetric Cost Functions

引用

conference on computer vision and pattern recognition (cvpr)

作者： Kuk-Jin Yoon In So Kweon Robotics and Computer Vision Laboratory Department Electrical Engineering and Computer Science KAIST Daejeon South Korea

Recently, many global stereo methods have achieved good results by modeling a disparity surface as a Markov random field (MRF) and by solving an optimization problem with various techniques. However, most global methods mainly focus on how to minimize conventional cost functions efficiently, although it is more important to define cost functions well to improve performance. In this paper, we propose new symmetric cost functions for global stereo methods. We first present a symmetric data cost function for the likelihood and then propose a symmetric discontinuity cost function for the prior in the MRF model for stereo. In defining cost function, both the reference image and the target image are taken into account to improve performance without modeling half-occluded pixels explicitly and without using color segmentation. The performance improvement of stereo matching due to the proposed symmetric cost functions is verified by applying the proposed symmetric cost functions to the belief propagation (BP) based stereo method. Experimental results for standard testbed images show that the performance of the BP based stereo method is greatly improved by the proposed symmetric cost functions.

关键词： Cost function Stereo vision Pixel computer vision Markov random fields Optimization methods Image segmentation Belief propagation Robot vision systems computer science

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A Mean Field EM-algorithm for Coherent Occlusion Handling in MAP-Estimation Prob

A Mean Field EM-algorithm for Coherent Occlusion Handling in...

引用

conference on computer vision and pattern recognition (cvpr)

作者： R. Fransens C. Strecha L. Van Gool K.U.Leuven ESAT-PSI Leuven Belgium

This paper presents a generative model based approach to deal with occlusions in vision problems which can be formulated as MAP-estimation problems. The approach is generic and targets applications in diverse domains like model-based object recognition, depth-from-stereo and image registration. It relies on a probabilistic imaging model, in which visible regions and occlusions are generated by two separate processes. The partitioning into visible and occluded regions is made explicit by the introduction of an hidden binary visibility map, which, to account for the coherent nature of occlusions, is modelled as a Markov Random Field. Inference is made tractable by a mean field EMalgorithm, which alternates between estimation of visibility and optimisation of model parameters. We demonstrate the effectiveness of the approach with two examples. First, in a N-view stereo experiment, we compute a dense depth map of a scene which is contaminated by multiple occluding objects. Finally, in a 2D-face recognition experiment, we try to identify people from partially occluded facial images.

关键词： Pixel Face recognition Image generation Optical imaging Face detection Noise generators pattern recognition Object recognition Image registration Markov random fields

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Visual landmarks detection and recognition for mobile robot navigation

Visual landmarks detection and recognition for mobile robot ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： J.B. Hayet F. Lerasle M. Devy LAAS CNRS Toulouse France

This article describes visual functions dedicated to the extraction and recognition of planar quadrangles detected from a single camera. Extraction is based on a relaxation scheme with constraints between image segments, while the characterization we propose allows recognition to be achieved from different view-points and viewing conditions. We defined and evaluated several metrics on this representation space - a correlation-based one and another one based on sets of interest points.

关键词： Mobile robots Navigation Robot vision systems Cameras Character recognition Image recognition Robustness Matched filters Image segmentation Extraterrestrial measurements

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Layered object detection for multi-class segmentation

Layered object detection for multi-class segmentation

引用

conference on computer vision and pattern recognition (cvpr)

作者： Yi Yang Sam Hallman Deva Ramanan Charless Fowlkes Department of Computer Science University of California Irvine USA

We formulate a layered model for object detection and multi-class segmentation. Our system uses the output of a bank of object detectors in order to define shape priors for support masks and then estimates appearance, depth ordering and labeling of pixels in the image. We train our system on the PASCAL segmentation challenge dataset and show good test results with state of the art performance in several categories including segmenting humans.

关键词： Object detection Image segmentation Detectors Shape Labeling Pixel computer science System testing Humans Benchmark testing

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Visual odometry and map correlation

Visual odometry and map correlation

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Levin R. Szeliski Microsoft Research Limited UK Hebrew University of Jerusalem Israel

In this paper we study how estimates of ego-motion based on feature tracking (visual odometry) can be improved using a rough (low accuracy) map of where the observer has been. We call the process of aligning the visual ego-motion with the map locations as map correlation. Since absolute estimates of camera position are unreliable, we use stable local information such as change in orientation to perform the alignment. We also detect when the observer's path has crossed back on itself which helps improve both the visual odometry estimates and the alignment between the video and map sequences. The final alignment is computed using a graphical model whose MAP estimate is inferred using loopy belief propagation. Results are presented on a number of indoor and outdoor sequences.

关键词： Cameras Robot vision systems Global Positioning System Yield estimation Motion estimation Simultaneous localization and mapping Graphical models Belief propagation Information resources Distance measurement

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The alignment of objects with smooth surfaces: error analysis of the curvature method

The alignment of objects with smooth surfaces: error analysi...

引用

conference on computer vision and pattern recognition (cvpr)

作者： R. Basri M. I. T. A. I. Laboratory Cambridge MA USA

The recognition of objects with smooth bounding surfaces from their contour images is addressed. In particular, the curvature method is applied to ellipsoidal objects and the error for different rotations of the objects is computed analytically. It is seen that the error depends on the exact shape of the ellipsoid (namely, the relative lengths of its axes), and it increases as the ellipsoid becomes elongated in the Z-direction. It is shown that the errors are usually small, and that, in general, a small number of models is required to predict the appearance of an ellipsoid from all possible views.< >

关键词： Error analysis Ellipsoids Shape Laboratories Predictive models Image recognition Object recognition Neuroscience Artificial intelligence Contracts

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A Rao-Blackwellized particle filter for EigenTracking

A Rao-Blackwellized particle filter for EigenTracking

引用

conference on computer vision and pattern recognition (cvpr)

作者： Zia Khan T. Balch F. Dellaert College of Computing Georgia Institute of Technology USA

Subspace representations have been a popular way to model appearance in computer vision. In Jepson and Black's influential paper on EigenTracking, they were successfully applied in tracking. For noisy targets, optimization-based algorithms (including EigenTracking) often fail catastrophically after losing track. Particle filters have recently emerged as a robust method for tracking in the presence of multi-modal distributions. To use subspace representations in a particle filter, the number of samples increases exponentially as the state vector includes the subspace coefficients. We introduce an efficient method for using subspace representations in a particle filter by applying Rao-Blackwellization to integrate out the subspace coefficients in the state vector. Fewer samples are needed since part of the posterior over the state vector is analytically calculated. We use probabilistic principal component analysis to obtain analytically tractable integrals. We show experimental results in a scenario in which we track a target in clutter.

关键词： Particle filters Target tracking computer vision Principal component analysis Shape Vectors Particle measurements Robustness Particle tracking State estimation

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Road markings detection and tracking using Hough Transform and Kalman filter

Road markings detection and tracking using Hough Transform a...

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7th International conference on Advanced Concepts for Intelligent vision Systems, ACIVS 2005

作者： Voisin, Vincent Avila, Manuel Emile, Bruno Begot, Stephane Bardet, Jean-Christophe Laboratoire Vision et Robotique IUT de l'Indre 36000 Châteauroux France Vectra Road Engineering 78320 La Verrière France

ISBN: (纸本)354029032X

A lane marking tracking method using Hough Transform and Kalman Filtering is presented. Since the HT is a global feature extraction algorithm, it leads to a robust detection relative to noise or partial occlusion. The Kalman filter is used to track the roadsides which are detected in the image by this HT. The Kalman prediction step leads to predict the road marking parameters in the next frame, so we can apply the detection algorithm in smaller regions of interest, the computional cost is being consequently reduced. © Springer-Verlag Berlin Heidelberg 2005.

关键词： pattern recognition

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Calibration of a foveated wide-angle lens on an active vision head

Calibration of a foveated wide-angle lens on an active visio...

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conference on computer vision and pattern recognition (cvpr)

作者： L. Berthouze S. Rougeaux F. Chavand Y. Kuniyoshi Autonomous Systems Section Electro Technical Laboratory Tsukuba Ibaraki Japan Equipe Systemes Complexes Centre dE28099Etudes Mecaniques dIE28099le de France Evry France

Inspired by the properties of the human visual system, a new active vision system called ESCHeR (Etl Stereo Compact Head For Robot vision) has been recently implemented with foveated wide angle lenses. The lenses exhibit a wide field of view along with a space-varying resolution for facilitating both detection and close observation. However, to handle such optical properties and achieve basic eye movement functions, new calibration methods are needed. Therefore, two novel and online techniques are presented that in one case perform a global identification of the optical process through artificial neural techniques and in the other case compute the physical parameters by using environmental feature-tracking and controlled rotations of the cameras. Self-alignment of the cameras is also achieved using a similar technique.

关键词： Calibration Lenses Cameras Humans Visual system Machine vision Orbital robotics Robot vision systems Optical computing Physics computing

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