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IEEE International Conference on image Processing

作者： David Weikersdorfer Alexander Schick Daniel Cremers Neuroscientific System Theory Technische Universit?t München Fraunhofer IOSB Karlsruhe Computer Vision & Image Analysis Technische Universit?t München

ISBN: (纸本)9781479923427

In this paper we present a method for automatic video segmentation of RGB-D video streams provided by combined colour and depth sensors like the Microsoft Kinect. To this end, we combine position and normal information from the depth sensor with colour information to compute temporally stable, depth-adaptive superpixels and combine them into a graph of strand-like spatiotemporal, depth-adaptive supervox-els. We use spectral graph clustering on the supervoxel graph to partition it into spatiotemporal segments. Experimental evaluation on several challenging scenarios demonstrates that our two-layer RGB-D video segmentation technique produces excellent video segmentation results.

关键词： Superpixels Supervoxels RGB-D Video Segmentation Video analysis Videotapes VIDEO analysis Line graph segmentation Segmentation Combine game player

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A highly efficient GPU implementation for variational optic flow based on the Euler-Lagrange framework

A highly efficient GPU implementation for variational optic ...

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11th European Conference on computer vision, ECCV 2010

作者： Gwosdek, Pascal Zimmer, Henning Grewenig, Sven Bruhn, Andrés Weickert, Joachim Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Saarland University Saarbrücken 66041 Germany Vision and Image Processing Group Cluster of Excellence Multimodal Computing and Interaction Saarland University Saarbrücken 66123 Germany

ISBN: (纸本)9783642357398

The Euler-Lagrange (EL) framework is the most widely-used strategy for solving variational optic flow methods. We present the first approach that solves the EL equations of state-of-the-art methods on sequences with pixels in near-realtime on GPUs. This performance is achieved by combining two ideas: (i) We extend the recently proposed Fast Explicit Diffusion (FED) scheme to optic flow, and additionally embed it into a coarse-to-fine strategy. (ii) We parallelise our complete algorithm on a GPU, where a careful optimisation of global memory operations and an efficient use of on-chip memory guarantee a good performance. Applying our approach to the variational 'Complementary Optic Flow' method (Zimmer et al. (2009)), we obtain highly accurate flow fields in less than a second. This currently constitutes the fastest method in the top 10 of the widely used Middlebury benchmark. © 2012 Springer-Verlag.

关键词： Graphics processing unit

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Evaluation of fast 2D and 3D medical image retrieval approaches based on image miniatures

Evaluation of fast 2D and 3D medical image retrieval approac...

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2nd MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CDS 2011

作者： Donner, René Haas, Sebastian Burner, Andreas Holzer, Markus Bischof, Horst Langs, Georg Computational Image Analysis and Radiology Lab. Department of Radiology Medical University of Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Austria Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA United States

ISBN: (纸本)9783642284595

The present work evaluates four medical image retrieval approaches based on features derived from image miniatures. We argue that due to the restricted domain of medical image data, the standardized acquisition protocols and the absence of a potentially cluttered background a holistic image description is sufficient to capture high-level image similarities. We compare four different miniature 2D and 3D descriptors and corresponding metrics, in terms of their retrieval performance: (A) plain miniatures together with euclidean distances in a k Nearest Neighbor based retrieval backed by kD-trees;(B) correlations of rigidly aligned miniatures, initialized using the kD-tree;(C) distribution fields together with the l1-norm;(D) SIFT-like histogram of gradients using the χ2-distance. We evaluate the approaches on two data sets: the imageClef 2009 benchmark of 2D radiographs with the aim to categorize the images and a large set of 3D-CTs representing a realistic sample in a hospital PACS with the objective to estimate the location of the query volume. © 2012 Springer-Verlag.

关键词： Medical imaging

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A Modified Gray level Co-occurrence Matrix based Thresholding for Object Background Classification

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Procedia Engineering 2012年 30卷 85-91页

作者： A. Dash P. Kanungo B.P. Mohanty Image Analysis & Computer Vision Lab. Department of ETC C. V. Raman College of Engineering Bhubaneswar 752054India bDepartment of EIE ITER S’O’A UniversityBhubaneswar-751030 India

Object background classification is the basic problem of object tracking in the computer vision area. Thresholding is the simplest approach to separate object from the background. The solutions using thresholding techniques become more complex when the image is blurred or low contrast. In this paper, we proposed a modified co-occurrence matrix for extraction of the edge information to detect the threshold for object and background classification in a low contrast or blurred image. The proposed approach is tested with standard test images which are of low contrast or blurred to different degree to validate the efficiency of our proposed method.

关键词： Gray level Co-occurrence matrix Thresholding Segmentation Misclassification Error

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Subspace Clustering

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IEEE SIGNAL PROCESSING MAGAZINE 2011年第2期28卷 52-68页

作者： Vidal, Rene He was coeditor of the book Dynamical Vision and has coauthored more than 100 articles in biomedical image analysis computer vision machine learning hybrid systems and robotics.

The past few years have witnessed an explosion in the availability of data from multiple sources and modalities. For example, millions of cameras have been installed in buildings, streets, airports, and cities around the world. This has generated extraordinary advances on how to acquire, compress, store, transmit, and process massive amounts of complex high-dimensional data.

关键词： Principal component analysis Polynomials Clustering algorithms Signal processing algorithms Noise Data models Subspace constraints

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Freehand HDR imaging of moving scenes with simultaneous resolution enhancement

Freehand HDR imaging of moving scenes with simultaneous reso...

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32nd Annual Conference on European Association for computer Graphics, EUROGRAPHICS 2011

作者： Zimmer, Henning Bruhn, Andrés Weickert, Joachim Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Saarland University Saarbrücken Germany Vision and Image Processing Group Cluster of Excellence Multimodal Computing and Interaction Saarland University Saarbrücken Germany

Despite their high popularity, common high dynamic range (HDR) methods are still limited in their practical applicability: They assume that the input images are perfectly aligned, which is often violated in practise. Our paper does not only free the user from this unrealistic limitation, but even turns the missing alignment into an advantage: By exploiting the multiple exposures, we can create a super-resolution image. The alignment step is performed by a modern energy-based optic flow approach that takes into account the varying exposure conditions. Moreover, it produces dense displacement fields with subpixel precision. As a consequence, our approach can handle arbitrary complex motion patterns, caused by severe camera shake and moving objects. Additionally, it benefits from several advantages over existing strategies: (i) It is robust under outliers (noise, occlusions, saturation problems) and allows for sharp discontinuities in the displacement field, (ii) The alignment step neither requires camera calibration nor knowledge of the exposure times. (Hi) It can be efficiently implemented on CPU and GPU architectures. After the alignment is performed, we use the obtained subpixel accurate displacement fields as input for an energy-based, joint super-resolution and HDR (SR-HDR) approach. It introduces robust data terms and anisotropic smoothness terms in the SR-HDR literature. Our experiments with challenging real world data demonstrate that these novelties are pivotal for the favourable performance of our approach. © 2010 The Author(s).

关键词： Pixels

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Segmentation of vertebrae using level sets with expectation maximization algorithm

Segmentation of vertebrae using level sets with expectation ...

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IEEE International Symposium on Biomedical Imaging

作者： Melih S. Aslan Aly A. Farag Ben Arnold Ping Xiang Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Image Analysis Inc. Columbia KY USA

ISBN: (纸本)9781424441273

In this paper, we propose a robust level sets method to segment vertebral bodies (VBs) in clinical computed tomography (CT) images. Since the VB and surrounding organs have very close gray level information and there are no strong edges in some CT images, the initialization of level sets method becomes very crucial step. If the object and background regions are not initialized correctly, the results would not be acceptable. Also, the size and place of the initial seed may give non-reproducible results. To solve these problems, we use a statistical level sets method which uses the Expectation- Maximization (EM) algorithm for the initialization and parameter estimation. Validity was analyzed using ground truths of data sets (expert segmentation) and the European Spine Phantom (ESP) as a known reference. The proposed method is compared with other known alternatives.

关键词： image segmentation Level set Bones Computed tomography Biomedical imaging Robustness Three dimensional displays

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A new shape based segmentation framework using statistical and variational methods

A new shape based segmentation framework using statistical a...

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IEEE International Conference on image Processing

作者： Melih S. Aslan Hossam Abdelmunim Aly A. Farag Ben Arnold Eslam Mostafa Ping Xiang Computer Vision and Image Processing Lab University of Louisville Louisville KY USA Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Computer and Systems Engineering Department Ain Shams University Cairo Egypt Image Analysis Inc Columbia KY USA

In this paper, we propose a new shape based segmentation and registration of the vertebral bodies (VBs) in clinical computed tomography (CT) images. The VB and surrounding organs have very close gray level information and there are no strong edges in some CT images. To overcome these challenges, image appearance and shape information of VBs are used. There are three phases of our experiments: i) the detection of the VB region using the Matched filter, ii) initial segmentation using the graph cuts which integrates the intensity and spatial interaction models, iii) registration of the shape priors and initially segmented region to obtain the final segmentation. Preliminary results show that our proposed algorithm gives very encouraging results and can solve many segmentation and registration problems.

关键词： image segmentation Shape Training Computed tomography Bones Accuracy Vectors

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A novel probabilistic simultaneous segmentation and registration using level set

A novel probabilistic simultaneous segmentation and registra...

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IEEE International Conference on image Processing

作者： Melih S. Aslan Eslam Mostafa Hossam Abdelmunim Ahmed Shalaby Aly A. Farag Ben Arnold Computer Vision and Image Processing Lab. University of Louisville Louisville KY USA Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Computer and Systems Engineering Department Ain Shams University Cairo Egypt Image Analysis Inc. Columbia KY USA

We propose a new shape-based segmentation approach using the statistical shape prior and level sets method. The segmentation depends on the image information and shape prior. Training shapes are grouped to form a probabilistic model. The shape model is embedded into the image domain taking in consideration the evolution of a contour represented by a level set function. The evolution of the front gathers information from the image intensities and shape prior. The segmentation approach is applied in segmenting the vertebral bodies in CT images. Our results shows that the technique is accurate and robust compared with the other alternative in the literature.

关键词： Shape image segmentation Level set Computed tomography Accuracy Probabilistic logic

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A new segmentation and registration approach for vertebral body analysis

A new segmentation and registration approach for vertebral b...

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IEEE International Symposium on Biomedical Imaging

作者： Melih S. Aslan Asem Ali Aly A. Farag Hossam Abdelmumin Ben Arnold Ping Xiang Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Computer and Systems Engineering Department Ain Shams University Cairo Egypt Image Analysis Inc. Columbia KY USA

To diagnose the osteoporosis accurately, the bone mineral density (BMD) measurements of the vertebral bodies (VBs) are required. In this paper, we propose a new segmentation and registration method in order to assist the BMD measurements and fracture analysis (FA) accurately. In this experiment, image appearance and shape information of VBs are used. Our shape model is required to be registered to the testing image to avoid user interaction(s). Our proposed framework has four phases: i) the detection of vertebral body (VB) using the Matched filter, ii) initial segmentation using the intensity and spatial interaction models, iii) the registration of the shape prior and initially segmented image by matching a vector distance function (VDF), and iv) final segmentation using graph cuts which integrates intensity, spatial interaction and shape prior. Preliminary results show that our new algorithm is very promising and can solve many segmentation and registration problems.

关键词： Shape image segmentation Three dimensional displays Computed tomography Bones Labeling image color analysis

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