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A Comparison of PMD-Cameras and Stereo-vision for the Task of Surface Reconstruction using Patchlets

A Comparison of PMD-Cameras and Stereo-Vision for the Task o...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Christian Beder Bogumil Bartczak Reinhard Koch Computer Science Department University of Kiel Kiel Germany

Recently real-time active 3D range cameras based on time-of-flight technology (PMD) have become available. Those cameras can be considered as a competing technique for stereo-vision based surface reconstruction. Since those systems directly yield accurate 3d measurements, they can be used for benchmarking vision based approaches, especially in highly dynamic environments. Therefore, a comparative study of the two approaches is relevant. In this work the achievable accuracy of the two techniques, PMD and stereo, is compared on the basis of patch-let estimation. As patchlet we define an oriented small planar 3d patch with associated surface normal. Least-squares estimation schemes for estimating patchlets from PMD range images as well as from a pair of stereo images are derived. It is shown, how the achivable accuracy can be estimated for both systems. Experiments under optimal conditions for both systems are performed and the achievable accuracies are compared. It has been found that the PMD system outperformed the stereo system in terms of achievable accuracy for distance measurements, while the estimation of normal direction is comparable for both systems.

关键词： Surface reconstruction Stereo vision Cameras Image reconstruction Application software Stereo image processing computer vision computer science Distance measurement Surface emitting lasers

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Kinematics from Lines in a Single Rolling Shutter Image

Kinematics from Lines in a Single Rolling Shutter Image

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Conference on computer vision and pattern recognition (CVPR)

作者： Omar Ait-Aider Adrien Bartoli Nicolas Andreff LASMEA (CNRS/UBP) Clermont Ferrand France

Recent work shows that recovering pose and velocity from a single view of a moving rigid object is possible with a rolling shutter camera, based on feature point correspondences. We extend this method to line correspondences. Owing to the combined effect of rolling shutter and object motion, straight lines are distorted to curves as they get imaged with a rolling shutter camera. Lines thus capture more information than points, which is not the case with standard projection models for which both points and lines give two constraints. We extend the standard line reprojection error, and propose a nonlinear method for retrieving a solution to the pose and velocity computation problem. A careful inspection of the design matrix in the normal equations reveals that it is highly sparse and patterned. We propose a blockwise solution procedure based on bundle-adjustment-like sparse inversion. This makes nonlinear optimization fast and numerically stable. The method is validated using real data.

关键词： Kinematics Cameras CMOS image sensors Nonlinear distortion Pixel Costs Sensor phenomena and characterization Signal to noise ratio Robot vision systems computer vision

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EDA Approach for Model Based Localization and recognition of Vehicles

EDA Approach for Model Based Localization and Recognition of...

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Conference on computer vision and pattern recognition (CVPR)

作者： Zhaoxiang Zhang Weishan Dong Kaiqi Huang Tieniu Tan National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences China

We address the problem of model based recognition. Our aim is to localize and recognize road vehicles from monocular images in calibrated scenes. A deformable 3D geometric vehicle model with 12 parameters is set up as prior information and Bayesian Classification Error is adopted for evaluation of fitness between the model and images. Using a novel evolutionary computing method called EDA (Estimation of Distribution Algorithm), we can not only determine the 3D pose of the vehicle, but also obtain a 12 dimensional vector which corresponds to the 12 shape parameters of the model. By clustering obtained vectors in the parameter space, we can recognize different types of vehicles. Experimental results demonstrate the effectiveness of the approach to vehicles of different types and poses. Thanks to EDA, we can not only localize and recognize vehicles, but also show the whole evolution procedure of the deformable model which gradually fits the image better and better.

关键词： Electronic design automation and methodology Deformable models Image recognition Solid modeling Road vehicles Layout Bayesian methods Distributed computing Clustering algorithms Shape

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Tracking complex objects using graphical object models

引用

1st International Workshop on Complex Motion, IWCM 2004

作者： Sigal, Leonid Ying, Zhu Comaniciu, Dorin Black, Michael Department of Computer Science Brown University Providence RI 02912 United States Integrated Data Systems Siemens Corporate Research Princeton NJ 08540 United States Real Time Vision and Modeling Siemens Corporate Research Princeton NJ 08540 United States

ISBN: (纸本)9783540698647

We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, where each node corresponds to an object or component of an object at a given time, and the edges correspond to learned spatial and temporal constraints. Object detection and tracking is formulated as inference over a directed loopy graph, and is solved with non-parametric belief propagation. This type of object model allows object-detection to make use of temporal consistency (over an arbitrarily sized temporal window), and facilitates robust tracking of the object. The two layer structure of the graphical model allows inference over the entire object as well as individual components. AdaBoost detectors are used to define the likelihood and form proposal distributions for components. Proposal distributions provide 'bottom-up' information that is incorporated into the inference process, enabling automatic object detection and tracking. We illustrate our method by detecting and tracking two classes of objects, vehicles and pedestrians, in video sequences collected using a single grayscale uncalibrated car-mounted moving camera. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Object recognition

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Isotropy, Reciprocity and the Generalized Bas-Relief Ambiguity

Isotropy, Reciprocity and the Generalized Bas-Relief Ambigui...

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Conference on computer vision and pattern recognition (CVPR)

作者： Ping Tan Satya P. Mallick Long Quan David J. Kriegman Todd Zickler Hong Kong University of Science and Technology Hong Kong China University of California San Diego USA Harvard School of Engineering and Applied Sciences USA

A set of images of a Lambertian surface under varying lighting directions defines its shape up to a three-parameter generalized bas-relief (GBR) ambiguity. In this paper, we examine this ambiguity in the context of surfaces having an additive non-Lambertian reflectance component, and we show that the GBR ambiguity is resolved by any non-Lambertian reflectance function that is isotropic and spatially invariant. The key observation is that each point on a curved surface under directional illumination is a member of a family of points that are in isotropic or reciprocal configurations. We show that the GBR can be resolved in closed form by identifying members of these families in two or more images. Based on this idea, we present an algorithm for recovering full Euclidean geometry from a set of uncalibrated photometric stereo images, and we evaluate it empirically on a number of examples.

关键词： Reflectivity Surface reconstruction Stereo vision Shape Spatial resolution Lighting Photometry computer vision Stereo image processing Image reconstruction

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Direction Code Based Features for recognition of Online Handwritten Characters of Bangla

Direction Code Based Features for Recognition of Online Hand...

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International Conference on Document Analysis and recognition

作者： U. Bhattacharya B.K. Gupta S. Parui Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

In the present article, we describe a novel direction code based feature extraction approach for recognition of online Bangla handwritten basic characters. We have implemented the proposed approach on a database of 7043 online handwritten Bangla (a major script of the Indian subcontinent) character samples, which has been developed by us. This is a 50-class recognition problem and we achieved 93.90% and 83.61% recognition accuracies respectively on its training and test sets.

关键词： Character recognition Handwriting recognition Spatial databases pattern recognition Histograms Shape Testing Personal digital assistants computer vision Feature extraction

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Toward Flexible 3D Modeling using a Catadioptric Camera

Toward Flexible 3D Modeling using a Catadioptric Camera

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Conference on computer vision and pattern recognition (CVPR)

作者： Maxime Lhuillier LASMEA UMR 6602 CNRS Université Blaise Pascal Aubiere France

Fully automatic 3D modeling from a catadioptric image sequence has rarely been addressed until now, although this is a long-standing problem for perspective images. All previous catadioptric approaches have been limited to dense reconstruction for a few view points, and the majority of them require calibration of the camera. This paper presents a method which deals with hundreds of images, and does not require precise calibration knowledge. In this context, the same 3D point of the scene may be visible and reconstructed in a large number of images at very different accuracies. So the main part of this paper concerns the selection of reconstructed points, a problem largely ignored in previous works. Summaries of the structure from motion and dense stereo steps are also given. Experiments include the 3D model reconstruction of indoor and outdoor scenes, and a walkthrough in a city.

关键词： Cameras Layout Image sequences Image reconstruction Calibration Image resolution Motion estimation Stereo vision Cities and towns computer vision

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Flash Cut: Foreground Extraction with Flash and No-flash Image Pairs

Flash Cut: Foreground Extraction with Flash and No-flash Ima...

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Conference on computer vision and pattern recognition (CVPR)

作者： Jian Sun Sing Bing Kang Zong-Ben Xu Xiaoou Tang Heung-Yeung Shum Microsoft Research Limited Redmond WA USA Xi’ an Jiaotong University Xi'an P. R. China Xi''an Jiaotong University Xi'an China Microsoft Research Redmond WA USA Microsoft Research Asia Beijing China Microsoft Research Asia Beijing P. R. China

In this paper, we propose a novel approach for foreground layer extraction using flash/no-flash image pairs, which we call flash cut. Flash cut is based on the simple observation that only the foreground is significantly brightened by the flash and the background appearance change is very small, if the background is distant. Changes due to flash, motion, and color information are fused in an MRF framework to produce high quality segmentation results. Flash cut handles some amount of camera shake, and foreground motion, which makes it practical for anyone with a flash-equipped camera to use. We validate our approach on a variety of indoor and outdoor examples.

关键词： Image segmentation Cameras Layout Stereo vision Image edge detection Asia Data mining computer vision Infrared imaging Robustness

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Real-Time License Plate recognition on an Embedded DSP-Platform

Real-Time License Plate Recognition on an Embedded DSP-Platf...

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Conference on computer vision and pattern recognition (CVPR)

作者： Clemens Arth Florian Limberger Horst Bischof Institute for Computer Graphics and Vision Graz University of Technology Graz Austria

In this paper we present a full-featured license plate detection and recognition system. The system is implemented on an embedded DSP platform and processes a video stream in real-time. It consists of a detection and a character recognition module. The detector is based on the AdaBoost approach presented by Viola and Jones. Detected license plates are segmented into individual characters by using a region-based approach. Character classification is performed with support vector classification. In order to speed up the detection process on the embedded device, a Kalman tracker is integrated into the system. The search area of the detector is limited to locations where the next location of a license plate is predicted. Furthermore, classification results of subsequent frames are combined to improve the class accuracy. The major advantages of our system are its real-time capability and that it does not require any additional sensor input (e.g. from infrared sensors) except a video stream. We evaluate our system on a large number of vehicles and license plates using bad quality video and show that the low resolution can be partly compensated by combining classification results of subsequent frames.

关键词： Licenses Streaming media Real time systems Detectors Infrared sensors Digital signal processing Character recognition Kalman filters Sensor systems Vehicles

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Joint Object Segmentation and Behavior Classification in Image Sequences

Joint Object Segmentation and Behavior Classification in Ima...

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Conference on computer vision and pattern recognition (CVPR)

作者： Laura Gui Jean-Philippe Thiran Nikos Paragios Signal Processing Institute Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland Laboratoire MAS Ecole Centrale de Paris Chatenay-Malabry France

In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial for both tasks, since it enables them to cooperate so that knowledge relevant to each can aid in the resolution of the other, thus enhancing the final result. In particular, classification offers dynamic probabilistic priors to guide segmentation, while segmentation supplies its results to classification, ensuring that they are consistent both with prior knowledge and with new image information. We demonstrate the effectiveness of our framework via a particular implementation for a hand gesture recognition application. The prior models are learned from training data using principal components analysis and they adapt dynamically to the content of new images. Our experimental results illustrate the robustness of our joint approach to segmentation and behavior classification in challenging conditions involving occlusions of the target object before a complex background.

关键词： Object segmentation Image sequences Image segmentation Active contours Shape Training data computer vision Level set Filtering Image recognition

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