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Rate distortion in image coding from embedded optimization constraints in vector quantization

Rate distortion in image coding from embedded optimization c...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Shuyu Yang S. Mitra Computer Vision & Image Analysis Laboratory Department of Electrical and Computer Engineering Texas Tech University Lubbock TX USA

ISBN: (纸本)0780370449

We compared the performance of two recently developed vector quantization algorithms using different optimization criteria for clustering, namely, the adaptive fuzzy leader clustering, a neuro-fuzzy algorithm, and the deterministic annealing, another unsupervised clustering algorithm based on probabilistic and statistical physics frameworks, with the rate distortion criterion as a performance measure. Such a comparison is useful for evaluating the efficiency of clustering algorithms for the purpose of image vector quantization instead of the conventional misclassification evaluation. This method is extended from the analysis of image coding in a spatial domain to sample vectors in the wavelet domain with predictable distribution. These sample vectors possess a multidimensional generalized Gaussian distribution through the new multi-scale feature extraction method. Our preliminary results show much improvement on the reconstructed image quality over JPEG.

关键词： Rate-distortion image coding Clustering algorithms Vector quantization Annealing Physics Distortion measurement image analysis Wavelet analysis Wavelet domain

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Very high accuracy velocity estimation using orientation tensors, parametric motion, and simultaneous segmentation of the motion field

Very high accuracy velocity estimation using orientation ten...

引用

8th International Conference on computer vision

作者： Farnebäck, G. Computer Vision Laboratory Department of Electrical Engineering Linköping University SE-581 83 Linköping Sweden

In [10] we presented a new velocity estimation algorithm, using orientation tensors and parametric motion models to provide both fast and accurate results. One of the tradeoffs between accuracy and speed was that no attempts were made to obtain regions of coherent motion when estimating the parametric models. In this paper we show how this can be improved by doing a simultaneous segmentation of the motion field. The resulting algorithm is slower than the previous one, but more accurate. This is shown by evaluation on the well-known Yosemite sequence, where already the previous algorithm showed an accuracy which was substantially better than for earlier published methods. This result has now been improved further.

关键词： image segmentation

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A new camera calibration method for robotic applications

A new camera calibration method for robotic applications

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： Jun-Sik Kim In-So Kweon Department of Electrical Engineering and Computer Science Robotics and Computer Vision Laboratory KAIST South Korea Department of Electrical Engineering and Computer Science KAIST South Korea

In this paper, we present a camera calibration method using two views of three pairs of concentric circles with known sizes. A new invariant property for circle is introduced to determine the position of the center of the projected circle. Given two image ellipses and their corresponding centers, a cross-ratio based method estimates the center of projected circles using the new invariant property. The accurate center of projected concentric circles provides correct correspondences between ellipses in the image plane and circles in 3D plane. We also demonstrate that two views of three pairs of coplanar concentric circles are enough to determine the intrinsic camera parameters, such as the focal length, the aspect ratio, and the principal point. We validate the performance of the method using both synthetic and real images. Our method shows a comparable performance with respect to similar calibration methods using planes. The use of concentric circles, however, provides correct correspondences between 3D target points and their image points, and greatly simplifies the calibration problem.

关键词： Robot vision systems Cameras Calibration Mobile robots Application software computer vision Laboratories computer science Layout Robot kinematics

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Very high accuracy velocity estimation using orientation tensors, parametric motion, and simultaneous segmentation of the motion field

Very high accuracy velocity estimation using orientation ten...

引用

International Conference on computer vision (ICCV)

作者： G. Farneback Computer Vision Laboratory Department of Electrical Engineering Linköping University Linkoping Sweden

ISBN: (纸本)0769511430

In a previous paper, the author presented a new velocity estimation algorithm, using orientation tensors and parametric motion models to provide both fast and accurate results. One of the tradeoffs between accuracy and speed was that no attempts were made to obtain regions of coherent motion when estimating the parametric models. In this paper we show how this can be improved by doing a simultaneous segmentation of the motion field. The resulting algorithm is slower than the previous one, but more accurate. This is shown by evaluation on the well-known Yosemite sequence, where already the previous algorithm showed an accuracy which was substantially better than for earlier published methods. This result has now been improved further.

关键词： Motion estimation Tensile stress image segmentation Filtering Stacking image sequences Spatiotemporal phenomena computer vision Laboratories Parametric statistics

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Articulated body posture estimation from multi-camera voxel data

Articulated body posture estimation from multi-camera voxel ...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： I. Mikic M. Trivedi E. Hunter P. Cosman Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California La Jolla CA USA

ISBN: (纸本)0769512720

We present a framework for articulated body model acquisition and tracking from voxel data. A 3D voxel reconstruction of the person's body is computed from silhouettes extracted from four cameras. The model acquisition process is fully automated. In the first frame, body parts are located sequentially. The head is located first, since its shape and size are unique and stable. Other parts are found by sequential template growing and fitting. This initial estimate of body part locations, sizes and orientations is then used as a measurement for the extended Kalman filter which ensures a valid articulated body model. The same filter, with a slightly modified state and state transition matrix, is then used for tracking. The performance of the system has been evaluated on several video sequences with promising results.

关键词： Cameras image reconstruction Biological system modeling Data mining computer vision Robot vision systems Head Shape Filters image segmentation

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Positioning and photo-mosaicking with long image sequences;comparison of selected methods

Positioning and photo-mosaicking with long image sequences;c...

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OCEANS

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

Despite limited range, high resolution and data rate are among factors motivating the investigation of vision-based technologies in support of unmanned submersible platform operations. Among many, automatic vision-guided station keeping, localization and navigation, photo-mosaicking and 3D mapping comprise application areas of special interest. The core issue in realizing these capabilities is to know with high accuracy the motion and (or) position of the vehicle. Over the last decade, a small, but growing, group of research centers have committed an extensive effort in underwater vision activities. Methods based on various approaches in motion vision- e.g., correlation-based, feature-based, optical flow-based, or direct are being developed and implemented in support of different applications on specialized platforms that may simultaneously utilize other sensors for positioning. This makes it somewhat difficult, for user groups unfamiliar with the methodologies or technologies, to evaluate the capabilities of these vision systems. The main motivation for this work was to carry out and report the results of experiments with various techniques for positioning and mosaicking, on the same data set.

关键词： image sequences Remotely operated vehicles Optical sensors Underwater vehicles Humans Sensor arrays Optical imaging National security Inspection Costs

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Model-based face tracking for dense motion field estimation

Model-based face tracking for dense motion field estimation

引用

Applied imagery Pattern Recognition Workshop (AIPR)

作者： T.F. Gee R.M. Mersereau Image Science and Machine Vision Group Oak Ridge National Laboratory Oak Ridge TN USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)0769512453

When estimating the dense motion field of a video sequence, if little is known or assumed about the content, a limited constraint approach such as optical flow must be used. Since optical flow algorithms generally use a small spatial area in the determination of each motion vector the resulting motion field can be noisy, particularly if the input video sequence is noisy. If the moving subject is known to be a face, then we may use that constraint to improve the motion field results. This paper describes a method for deriving dense motion field data using a face tracking approach. A face model is manually initialized to fit a face at the beginning of the input sequence. Then a Kalman filtering approach is used to track the face movements and successively fit the face model to the face in each frame. The 2D displacement vectors are calculated from the projection of the facial model, which is allowed to move in 3D space and may have a 3D shape. We have experimented with planar, cylindrical, and Candide face models. The resulting motion field is used in multiple frame restoration of a face in noisy video.

关键词： Tracking Motion estimation Video sequences Optical filters image motion analysis Optical noise Kalman filters Filtering Shape Multi-stage noise shaping

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An ROC analysis for subpixel detection

An ROC analysis for subpixel detection

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chein-I Chang Shao-Shan Chiang Qian Du Hsuan Ren A. Ifarragaerri Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA Department of Computer Science and Electrical Engineering Texas A and M University Kingsville TX USA Biological and Chemical Command US Army MD USA

ROC (Receiver Operating Characteristic) analysis has been widely used to evaluate detection performance. It is based on the Neyman-Pearson detection theory, which solves binary hypothesis testing problems. In mixed pixel classification many algorithms that are developed to estimate abundance fractions (of image endmembers) generally produce gray scale images. As a result, they are not directly applied to hypothesis testing problems. Instead of using the standard ROC curve generated by the detection power versus the false alarm probability, a 3-dimensional (3D) ROC curve is developed in this paper for subpixel detection. It is a 3D plot derived from the mean-detection probability versus the mean-false alarm rate with the third dimension specified by abundance fractions produced by subpixel detection algorithms. In order to illustrate the utility of the proposed 3D ROC analysis in subpixel detection, several linear unmixing-based algorithms are used for performance evaluation.

关键词： Testing Pixel Performance analysis computer science Chemical analysis image segmentation Signal processing image processing Laboratories Chemical processes

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Segmentation and analysis of leg ulcers color images

Segmentation and analysis of leg ulcers color images

引用

International Workshop on Medical Imaging and Augmented Reality

作者： A.A. Perez A. Gonzaga J.M. Alves Computer Vision Laboratory Department of Electrical Engineering School of Engineering of São Carlos University of São Paulo Sao Paulo Brazil Department of Materials Aeronautic and Automotive Engineering School of Engineering of São Carlos University of São Paulo Bioengineering Graduate Program Sao Paulo Brazil

ISBN: (纸本)0769511139

This paper presents a methodology for the segmentation and analysis of the tissues in color images of leg ulcers. The segmentation is obtained through an automatic analysis made in the RGB and SI channels by changing from the RGB color space to the HSI color space. The aim is to determine which of the five channels have the characteristic that will make the segmentation process more efficient. After the analysis, the selected channel is segmented and used as a mask over the original image, allowing that only the inner tissues of the wound be analyzed. The analysis is done through predetermined functions that attribute membership grade for each processed pixel as well as its level of engagement in a specified tissue class. The article also shows the results obtained from both the segmentation and analysis of tissues using the proposed method.

关键词： image segmentation image analysis image color analysis Leg Wounds Cameras Automotive engineering Colored noise Monitoring Video compression

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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3rd International Conference on Information Fusion, FUSION 2000

作者： Mostafa, Mostafa G. Farag, Aly A. Essock, Edward Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY 40292 United States Department of Psychology University of Louisville Louisville KY 40292 United States

ISBN: (纸本)2725700000

Multi-modality image registration and fusion are essential steps in building 3D models from remote sensing data. In this paper, we present a neural network technique for the registration and fusion of multi-modality remote sensing data for the reconstruction of 3D models of terrain regions. A feedforward neural network is used to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data are presented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusion results. © 2000 Int. Soc. Inf. Fusion.

关键词： image fusion

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