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作者： P. Firoozfam S. Negahdaripour C. Barufaldi Underwater Vision & Imaging Lab Electrical and Computer Engineering Department University of Miami Coral Gables FL USA

The concept of a "conical panorama" was introduced in an earlier paper, involving the view of an oblique down-look camera rotating about an axis, either directly through or at some distance from the center of projection. This provides the framework 1) to analyze multi-camera realizations developed for various underwater visual tasks, and 2) to develop methods for the computation of visual motion that are more robust relative to processing of images covering a finite field of view. This paper presented a stereo conical imaging system, comprising 12 cameras with relatively large overlap between pairs of neighboring cameras. This panoramic stereovision system is targeted for 3-D visualization and improved scene reconstruction by utilizing correspondences in more than 2 views of the scene at modest distances. The calibration of the system is addressed, and experimental results demonstrate the potential in the use of this system for 3-D mapping.

关键词： Stereo image processing Layout Image reconstruction Cameras Image analysis Image motion analysis Motion analysis Robustness Galois fields Visualization

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On reconstruction of 3-D volumetric models of reefs and benthic structures from image sequences of a stereo rig

On reconstruction of 3-D volumetric models of reefs and bent...

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OCEANS

作者： Hongsheng Zhang S. Negahdaripour Underwater Vision & Imaging Lab Electrical and Computer Engineering Department University of Miami Coral Gables FL USA

Acquiring 3-D computer models of objects from images has been an active computer vision research topic. A common approach uses overlapping images from different views around the object, and attempts to fuse all the information to construct the model by volume intersection. Most current methods have in common that the camera poses for these views are known. To achieve this, a monocular camera circles the target object on a robot arm, or equivalently, views a target on a rotating platform (e.g., a turntable), while the images are acquired at known intervals. We are interested in the deployment of a submersible platform equipped with stereo vision to construct 3-D volumetric models of benthic habitat objects, e.g., coral reefs and other seafloor structures. In this application, we would automatically acquire continuous 360-degrees stereo views of object(s) of interest, by processing the images online to estimate and control camera trajectory and views. In particular, we show that the redundancy from binocular cues improves the robustness and accuracy. Upon completion of the image data acquisition, a bundle adjustment formulation is proposed to recompute the trajectory and the stereo rig poses, as well as to generate object model(s).

关键词： Image reconstruction Image sequences Stereo image processing Stereo vision Cameras computer vision Robot vision systems Fuses Underwater vehicles Sea floor

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Robust optical flow estimation using underwater color images

Robust optical flow estimation using underwater color images

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OCEANS

作者： S. Negahdaripour H. Madjidi Underwater Vision & Imaging Lab Electrical and Computer Engineering Department University of Miami Coral Gables FL USA

Accurate and efficient optical flow estimation is a major step in many computational vision problems, including 3-D mapping applications. While processing of gray scale image sequences has been the main approach, some authors have recently investigated and reported the use of color images. The main advantage in the use of color images is to exploit redundant information at each pixel, namely 3 channels, as potential cues for visual motion. Moreover, several spectral-dependent factors including medium attenuation may justify the use of color cues in underwater, calling for a physics-based approach to optical flow analysis. This paper explores a simplified underwater image formation model 1) to provide some preliminary insight on the information encoded in various color channels, 2) draw some general conclusions on the use of color and its various representations, and 3) verify if the results are consistent with the experiments with 7 sets of coral reef video recoded in relatively clear shallow waters of the Bahamas. These results suggest that optical flow algorithms based on the HSV representation can provide improved localization and accuracy.

关键词： Image motion analysis Color Optical attenuators Optical computing Optical filters Optical noise Noise robustness Brightness Optical imaging computer vision

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Statistically Robust Approach to Lens Distortion Calibration with Model Selection

Statistically Robust Approach to Lens Distortion Calibration...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Moumen Taha El-Melegy Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Dept. Assiut University Assiut Egypt Computer Vision and Image Processing Lab. University of Louisville Louisville KY

This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. While almost all existing nonmetric distortion calibration methods need user involvement in one form or another,we present an approach to distortion calibration based on the robust the-least-median-of-squares (LMedS) estimator. Our approach is thus able to proceed in a ful ly-automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered as projections of 3D linear segments. Our approach uniquely uses fast, closed-form solutions to the distortion coefficients, which serve as an initial point for a non-linear optimization algorithm to straighten imaged lines. Moreover we propose a method for distortion model selection based on geometrical *** experiments to evaluate the performance of this approach on synthetic and real data are reported.

关键词： Nonlinear distortion Calibration Robustness Lenses Cameras Image edge detection Distortion measurement

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Evaluation of 3D correspondence methods for model building

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18th International Conference on Information Processing in Medical Imaging, IPMI 2003

作者： Styner, Martin A. Rajamani, Kumar T. Nolte, Lutz-Peter Zsemlye, Gabriel Székely, Gábor Taylor, Chris J. Davies, Rhodri H. M E Müller Institute for Surgical Technology and Biomechanics University of Bern P O Box 8354 Bern3001 Switzerland Computer Vision Lab ETH-Zentrum Gloriastrasse 35 Zürich8092 Switzerland Division of Imaging Science and Biomedical Engineering University of Manchester Stopford Building Oxford Road ManchesterM13 9PT United Kingdom

ISBN: (纸本)3540405607

The correspondence problem is of high relevance in the constructionand use of statistical models. Statistical models are used for avariety of medical application, e.g. segmentation, registration and shapeanalysis. In this paper, we present comparative studies in three anatomicalstructures of four different correspondence establishing *** goal in all of the presented studies is a model-based *** have analyzed both the direct correspondence via manually selectedlandmarks as well as the properties of the model implied by the correspondences,in regard to compactness, generalization and specificity. Thestudied methods include a manually initialized subdivision surface (MSS)method and three automatic methods that optimize the object parameterization:SPHARM, MDL and the covariance determinant (DetCov)method. In all studies, DetCov and MDL showed very similar *** model properties of DetCov and MDL were better than SPHARMand MSS. The results suggest that for modeling purposes the best of thestudied correspondence method are MDL and DetCov. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Medical applications

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Using intrinsic images for shadow handling 5

Using intrinsic images for shadow handling

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5th IEEE International Conference on Intelligent Transportation Systems, ITSC 2002

作者： Martin, Robert F.K. Masoud, Osama Papanikolopoulos, Nikolaos Department of Computer Science and Engineering Artificial Intelligence Vision and Robotics Lab University of Minnesota United States

ISBN: (纸本)0780373898

The ability to detect shadows Is a critical feature of any Intelligent transportation system (ITS). The Improper handling of shadows can be the cause of erroneous conclusions in traffic analysis. Because vision-based ITS applications are becoming more popular, It la Important to minimize the fillets of shadows. Here, we present a novel method for shadow handling in a sequences of Images, fallowing recent work motivated by studies of the statistics of natural Images, we show that this new method Is a reliable detector of shadows and can be easily Implemented In real time. © 2002 IEEE.

关键词： Intelligent systems

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution(MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

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16th International Conference on Pattern Recognition, ICPR 2002

作者： Jun, Xie Tsui, H.T. Deshen, Xia Image Processing and Computer Vision Lab Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Pattern Recognition Lab Department of Computer Science Nanjing University of Sci.andTech. China

ISBN: (纸本)0769516963

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties . The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples Its performance in the experiments is better than those of two popular methods. © 2002 IEEE.

关键词： Maximum likelihood estimation

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Image Database for Automatic Face Recognition

Image Database for Automatic Face Recognition

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Proceedings of the 6th Joint Conference on Information Sciences, JCIS 2002

作者： Singh, S.K. Lokesh, R.B. Vatsa, Mayank Singh, Richa Dept. of Comp. Sc. And Engineering Inst. of Engineering and Technology VBS Purvanchal University Jaunpur India Computer Vision Lab Dept. of Electrical Engg. IISc Banglore India

In automatic face recognition, the management of image database has its own importance. At present there are two large databases that are being used for most of the face recognition algorithms, they are FERET and XM2V... 详细信息

ISBN: (纸本)0970789017

关键词： Face recognition

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A hierarchical approach to robust background subtraction using color and gradient information

A hierarchical approach to robust background subtraction usi...

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Workshop on Motion and Video Computing

作者： O. Javed K. Shafique M. Shah Computer Vision Lab School of Electrical Engineering and Computer Science University of Central Florida USA

We present a background subtraction method that uses multiple cues to detect objects robustly in adverse conditions. The algorithm consists of three distinct levels, i.e., pixel level, region level and frame level. At the pixel level, statistical models of gradients and color are separately used to classify each pixel as belonging to background or foreground. In the region level, foreground pixels obtained from the color based subtraction are grouped into regions and gradient based subtraction is then used to make inferences about the validity of these regions. Pixel based models are updated based on decisions made at the region level. Finally, frame level analysis is performed to detect global illumination changes. Our method provides the solution to some of the common problems that are not addressed by most background subtraction algorithms, such as fast illumination changes, repositioning of static background objects, and initialization of background model with moving objects present in the scene.

关键词： Robustness Lighting Layout Pixel Object detection Surveillance computer vision computer science Performance analysis Inference algorithms

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Visual content-based segmentation of talk and game shows

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International Journal of computers and Applications 2002年第2期24卷 77-82页

作者： Javed, O. Khan, S. Rasheed, Z. Shah, M. Computer Vision Lab School of Electrical Engineering University of Central Florida Orlando FL 32816 United States

In this article we present a method to remove commercials from talk and game show videos and to segment these videos into host and guest shots. In our approach, we rely mainly on information contained in shot transitions, rather than analyzing the scene content of individual frames. We utilize the inherent difference in scene structure of commercials and talk shows to differentiate between them. Similarly, we make use of the well-defined structure of talk shows, which can be exploited to classify shots as host or guest shots. The entire show is first segmented into camera shots based on colour histogram. Then we construct a data-structure (shot connectivity graph) that links similar shots over time. Analysis of the shot connectivity graph helps us to automatically separate commercials from program segments. This is done by first detecting stories and then assigning a weight to each story based on its likelihood of being a commercial. Further analysis on stories is done to distinguish shots of the hosts from shots of the guests. We have tested our approach on several full-length shows (including commercials) and have achieved video segmentation with high accuracy. The whole scheme is fast and works even on low-quality video (160×120 pixel images at 5 Hz).

关键词： Image segmentation

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