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Robust Estimation in the Presence of Spatially Coherent Outliers

Robust Estimation in the Presence of Spatially Coherent Outl...

引用

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

作者： R. Fransens C. Strecha L. Van Gool ESAT-PSI Katholieke Universiteit Leuven Leuven Belgium

We present a generative model based approach to deal with spatially coherent outliers. The model assumes that image pixels are generated by either one of two distinct processes: an inlier process which is responsible for the generation of the majority of the data, and an outlier process which generates pixels not adhering to the inlier model. The partitioning into inlier and outlier regions is made explicit by the introduction of a hidden binary map. To account for the coherent nature of outliers this map is modelled as a Markov Random Field, and inference is made tractable by a mean field EM-algorithm. We make a connection with classical robust estimation theory, and derive the analytic expressions of the equivalent M-estimator for two limiting cases of our model. The effectiveness of the proposed method is demonstrated with two examples. First, in a synthetic linear regression problem, we compare our approach with different M-estimators. Next, in a 2D-face recognition experiment, we try to identify people from partially occluded facial images.

关键词： Robustness Spatial coherence Additive noise Pixel Face recognition computer vision Parameter estimation Image generation Image recognition Layout

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Multi-view Appearance-based 3D Hand Pose Estimation

Multi-view Appearance-based 3D Hand Pose Estimation

引用

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

作者： Haiying Guan Jae Sik Chang Longbin Chen R.S. Feris M. Turk Computer Science Department University of California Santa Barbara CA USA

We describe a novel approach to appearance-based hand pose estimation which relies on multiple cameras to improve accuracy and resolve ambiguities caused by selfocclusions. Rather than estimating 3D geometry as most previous multi-view imaging systems, our approach uses multiple views to extend current exemplar-based methods that estimate hand pose by matching a probe image with a large discrete set of labeled hand pose images. We formulate the problem in a MAP (maximum a posteriori) framework, where the information from multiple cameras is fused to provide reliable hand pose estimation. Our quantitative experimental results show that correct estimation rate is much higher using our multi-view approach than using a single-view approach.

关键词： Cameras Probes Three dimensional displays computer displays Feature extraction computer science Geometry Large-scale systems Personal digital assistants Cellular phones

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Combining Regions and Patches for Object Class Localization

Combining Regions and Patches for Object Class Localization

引用

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

作者： C. Pantofaru G. Dorko C. Schmid M. Hebert The Robotics Institute CMU USA TU Darmstadt Germany INRIA Rhone-Alpes France

We introduce a method for object class detection and localization which combines regions generated by image segmentation with local patches. Region-based descriptors can model and match regular textures reliably, but fail on parts of the object which are textureless. They also cannot repeatably identify interest points on their boundaries. By incorporating information from patch-based descriptors near the regions into a new feature, the Region-based Context Feature (RCF), we can address these issues. We apply Region-based Context Features in a semi-supervised learning framework for object detection and localization. This framework produces object-background segmentation masks of deformable objects. Numerical results are presented for pixel-level performance.

关键词： Object detection Shape Labeling Image segmentation Smart pixels Intelligent robots Image generation Semisupervised learning computer vision Layout

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Cinematized Reality: Cinematographic 3D Video System for Daily Life Using Multiple Outer/Inner Cameras

Cinematized Reality: Cinematographic 3D Video System for Dai...

引用

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

作者： Hansung Kim R. Sakamoto K. Kogure I. Kitahara Media Information Science Laboratory ATR Keihanna Science City Kyoto Japan Department of Intelligent Interaction Technologies University of Tsukuba Tsukuba Ibaraki Japan

The purpose of Cinematized Reality is to record unexpected moments in people’s lives and create movies that look as if they were created from real, expertly captured film footage. The approach toward Cinematized Reality is to generate free-view video streams from multiple videos. The proposed system reconstructs 3D models of the capturing space using outer environmental cameras and an inner omni-directional camera, and then generates realistic video of those objects from a designated viewpoint by controlling a virtual camera as an expert would. This prototype system follows the grammar of film language and applies expert knowledge to generate desirable film footage using a sequence of shots taken by the virtual camera.

关键词： Calibration Videoconference Network servers Cities and towns Layout Instruments Shape measurement Smart cameras Information science computer vision

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Multiresolution Approach for Non-Contact Measurements of Arterial Pulse using Thermal Imaging

Multiresolution Approach for Non-Contact Measurements of Art...

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

作者： S.Y. Chekmenev A.A. Farag E.A. Essock Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Department of Psychological and Brain University of Louisville Louisville KY USA

This paper presents a novel, multiresolution (MR) approach for non-contact passive measurements of the arterial pulse along the arterial tree using thermal imaging of the most accessible regions of human face and neck. The method automatically detects Region/s Of Measurement (ROM) of the arterial pulse using the periodic nature of arterial thermal patterns. This ROM constitutes a skin area where the heat pulsation produced by an artery is most pronounced. The output of the algorithm is a descriptive arterial pulse waveform. To the best of our knowledge, our results are novel and have not been reported before. Some potential applications of this work are in the field of non-contact health state/ physiology monitoring, magnetic resonance imaging, smart rooms, polygraph testing, and intent identification.

关键词： Pulse measurements Image resolution Read only memory Humans Face detection Neck Skin Arteries Physiology Monitoring

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Strangeness Based Feature Selection for Part Based recognition

Strangeness Based Feature Selection for Part Based Recogniti...

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

作者： Fayin Li J. Kosecka H. Wechsler George Mason University Fairfax VA USA

Motivated by recent approaches to object recognition, where objects are represented in terms of parts, we propose a new algorithm for selecting discriminative features based on strangeness measure. We will show that k-nearest neighbour strangeness can be used to measure the uncertainty of individual features with respect to the class labels and forms piecewise constant decision boundary. We study its properties and generalization capability by comparing it with optimal decision boundary and boundary obtained by k-nearest-neighbor methods. The proposed feature selection algorithm is tested both in simulation and real experiments, demonstrating that meaningful discriminative local features are selected despite the presence of large numbers of distractors. In the second stage we demonstrate how to integrate the local evidence provided by the selected features in the boosting framework in order to obtain the final strong classifier. The performance of the feature selection algorithm and the classifier is evaluated on the Caltech five object category database, achieving superior results in comparison with existing approaches at lower computational cost.

关键词： computer vision Object recognition Testing Supervised learning Vocabulary Boosting Spatial databases Computational efficiency Predictive models Data visualization

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Model-Driven Video-Based Rendering for Vehicles

Model-Driven Video-Based Rendering for Vehicles

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

作者： I.O. Sebe Suya You U. Neumann Computer Graphics and Immersive Technologies Laboratory Los Angeles CA USA

We present a video-based rendering (VBR) method that creates arbitrary views of the scene from images captured by a single un-calibrated camera. The system is model-based and focused on a single object class, specifically vehicles in this paper. The procedure has three main steps. First, the object is rapidly modeled from a single image using a simple interactive tool. The modeling tool creates high quality 3D models by facilitating constrained modifications to a generic model of the object class. Secondly, the dynamic object is tracked in the video sequence and the pose of the object is recorded. The tracking and pose estimation leverage the 3D model to ensure high accuracy. Lastly, the surrounding scene is modeled as a textured piece-wise planar approximation. A free-viewpoint rendering of the video (4D video) is then produced as needed for special effects or virtual reality applications. The versatility and effectiveness of our approach to modeling and rendering is demonstrated on the object class of vehicles.

关键词： Vehicles Rendering (computer graphics) Cameras Laser modes Mice Hardware Buildings computer graphics Laboratories computer vision

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Reinforcement Matching Using Region Context

Reinforcement Matching Using Region Context

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

作者： Hongli Deng E.N. Mortensen L. Shapiro T.G. Dietterich Electrical Engineering and Computer Science Oregon State University USA Computer Science and Engineering University of Washington USA

Local feature-based matching is robust to both clutter and occlusion. However, a primary shortcoming of local features is a deficiency of global information that can cause ambiguities in matching. Local features combined with global relationships convey much more information, but global spatial information is often not robust to occlusion and/or non-rigid transformations. This paper proposes a new framework for including global context information into local feature matching, while still maintaining robustness to occlusion, clutter, and nonrigid transformations. To generate global context information, we extend previous fixed-scale, circular-bin methods by using affine-invariant log-polar elliptical bins. Further, we employ a reinforcement matching scheme that provides greater robustness to occlusion and clutter than previous methods that non-discriminately compare accumulated bins values over the entire context. We also present a more robust method of calculating a feature’s dominant orientation. We compare reinforcement matching to nearest neighbor matching without region context and to robust matching methods (RANSAC and PROSAC).

关键词： computer vision computer science Solid modeling Euclidean distance Shape Histograms pattern recognition conferences Robustness

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Segmentation of fMRI Data by Maximization of Region Contrast

Segmentation of fMRI Data by Maximization of Region Contrast

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

作者： P.S. Mitra V. Gopalakrishnan R.L. McNamee Center for Biomedical Informatics University of Pittsburgh USA Departments of Pharmaceutical Sciences & Bioengineering University of Pittsburgh USA

Functional segmentation of an fMRI image is the partitioning of the image voxels into clumps that are comodulated by task-related neural activation or other processes. This grouping of voxels can be useful for exploratory analysis and for detection of signal artifacts that can confound regression-based analysis. We present a new method for functional segmentation that is based upon maximization of the contrast of an image-region with respect to its spatial neighborhood. Contrast maximization is an appealing approach since it does not require imagespecific tuning of parameters, as with many clustering approaches. With synthetic benchmark datasets, the accuracy of this Auto-threshold Contrast Enhancing Iterative Clustering (ACEIC) method compares favorably with that of Probabilistic ICA, which is a popular method used for detection of functional groupings of voxels. We also show that functional segmentation of in vivo datasets with ACEIC can provide insights into the results from conventional analysis.

关键词： Independent component analysis Image segmentation Clustering methods Size control Biomedical informatics Pharmaceuticals Biomedical engineering computer vision pattern recognition conferences

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A Camera-Projector System for Robot Positioning by Visual Servoing

A Camera-Projector System for Robot Positioning by Visual Se...

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

作者： J. Pages C. Collewet F. Chaumette J. Salvi Institut d'Informàtica i Aplicacions University of Girona Girona Spain IRISA INRIA-Rennes Rennes France IRISA INRIA-Rennes Institut d'Informàtica i Aplicacions

Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance.

关键词： Visual servoing Feature extraction Robot sensing systems Robot vision systems Cameras Data mining Robustness computer vision Proposals Robot control

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