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Gabor Filter Analysis for Texture Segmentation

Gabor Filter Analysis for Texture Segmentation

引用

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

作者： R. Sandler M. Lindenbaum Computer Science Department Technion-Israel Institute of Technology Haifa Israel

Gabor features are a common choice for texture analysis. The particular set of Gabor filters used for extracting the features is usually designed for optimal signal representation. We propose here an alternative criterion for designing the filter set. We consider a set of filters and its response to pairs of harmonic signals. Two signals are considered separable if the corresponding two sets of vector responses are disjoint in at least one of the components. We look for the set of Gabor filters that maximizes the fraction of separable harmonic signal pairs. The resulting filters are significantly different from the traditional ones. We test these maximal harmonic discrimination (MHD) filters using two texture discrimination methods, and describe their advantages over traditional filters.

关键词： Gabor filters Power harmonic filters Image segmentation Signal design Distortion measurement Signal analysis Stability Harmonic analysis computer science Feature extraction

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A Closed Form Solution to Natural Image Matting

A Closed Form Solution to Natural Image Matting

引用

conference on computer vision and pattern recognition (CVPR)

作者： A. Levin D. Lischinski Y. Weiss School of Computer Science and Engineering Hebrew University of Jerusalem Israel

Interactive digital matting, the process of extracting a foreground object from an image based on limited user input, is an important task in image and video editing. From a computer vision perspective, this task is extremely challenging because it is massively ill-posed - at each pixel we must estimate the foreground and the background colors, as well as the foreground opacity ("alpha matte") from a single color measurement. Current approaches either restrict the estimation to a small part of the image, estimating foreground and background colors based on nearby pixels where they are known, or perform iterative nonlinear estimation by alternating foreground and background color estimation with alpha estimation. In this paper we present a closed form solution to natural image matting. We derive a cost function from local smoothness assumptions on foreground and background colors, and show that in the resulting expression it is possible to analytically eliminate the foreground and background colors to obtain a quadratic cost function in alpha. This allows us to find the globally optimal alpha matte by solving a sparse linear system of equations. Furthermore, the closed form formula allows us to predict the properties of the solution by analyzing the eigenvectors of a sparse matrix, closely related to matrices used in spectral image segmentation algorithms. We show that high quality mattes can be obtained on natural images from a surprisingly small amount of user input.

关键词： Closed-form solution Cost function Image color analysis Sparse matrices computer vision Pixel Iterative methods Linear systems Equations Image analysis

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Moving Object Localization in Thermal Imagery by Forward-backward MHI

Moving Object Localization in Thermal Imagery by Forward-bac...

引用

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

作者： Zhaozheng Yin R. Collins Department of Computer Science and Engineering Pennsylvania State University University Park PA USA

Detecting moving objects automatically is a key component of an automatic visual surveillance and tracking system. In airborne thermal video, the moving objects may be small, color information is not available, and even intensity appearance may be camouflaged. Previous motionbased moving object detection approaches often use background subtraction, inter-frame difference or three-frame difference. In this paper, we describe a detection and localization method based on forward-backward motion history images (MHI). This method can accurately detect location and shape of moving objects for initializing a tracker. Using long and varied video sequences, we quantify the effectiveness of this method.

关键词： Object detection Shape Motion detection Cameras Surveillance Image reconstruction Thermal engineering computer science History Video sequences

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Deformation Modeling for Robust 3D Face Matching

Deformation Modeling for Robust 3D Face Matching

引用

conference on computer vision and pattern recognition (CVPR)

作者： Xiaoguang Lu A.K. Jain Department of Computer Science & Engineering Michigan State University East Lansing MI USA

Human face recognition based on 3D surface matching is promising for overcoming the limitations of current 2D image-based face recognition systems. The 3D shape is invariant to the pose and lighting changes, but not invariant to the non-rigid facial movement, such as expressions. Collecting and storing multiple templates for each subject in a large database (associated with various expressions) is not practical. We present a facial surface modeling and matching scheme to match 2.5D test scans in the presence of both non-rigid deformations and large pose changes (multiview) to a neutral expression 3D face model. A geodesic-based resampling approach is applied to extract landmarks for modeling facial surface deformations. We are able to synthesize the deformation learned from a small group of subjects (control group) onto a 3D neutral model (not in the control group), resulting in a deformed template. A personspecific (3D) deformable model is built for each subject in the gallery w.r.t. the control group by combining the templates with synthesized deformations. By fitting this generative deformable model to a test scan, the proposed approach is able to handle expressions and large pose changes simultaneously. Experimental results demonstrate that the proposed matching scheme based on deformation modeling improves the matching accuracy.

关键词： Deformable models Robustness Face recognition Humans Shape Testing Mouth computer science Image databases Control system synthesis

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Lensless Imaging with a Controllable Aperture

Lensless Imaging with a Controllable Aperture

引用

conference on computer vision and pattern recognition (CVPR)

作者： A. Zomet S.K. Nayar Computer Science Department Columbia University New York NY USA

In this paper we propose a novel, highly flexible camera. The camera consists of an image detector and a special aperture, but no lens. The aperture is a set of parallel light attenuating layers whose transmittances are controllable in space and time. By applying different transmittance patterns to this aperture, it is possible to modulate the incoming light in useful ways and capture images that are impossible to capture with conventional lens-based cameras. For example, the camera can pan and tilt its field of view without the use of any moving parts. It can also capture disjoint regions of interest in the scene without having to capture the regions in between them. In addition, the camera can be used as a computational sensor, where the detector measures the end result of computations performed by the attenuating layers on the scene radiance values. These and other imaging functionalities can be implemented with the same physical camera and the functionalities can be switched from one video frame to the next via software. We have built a prototype camera based on this approach using a bare image detector and a liquid crystal modulator for the aperture. We discuss in detail the merits and limitations of lensless imaging using controllable apertures.

关键词： Apertures Cameras Detectors Layout Lenses Lighting control Optical modulation Attenuation measurement Performance evaluation Software prototyping

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Using Dependent Regions for Object Categorization in a Generative Framework

Using Dependent Regions for Object Categorization in a Gener...

引用

conference on computer vision and pattern recognition (CVPR)

作者： Gang Wang Ye Zhang Li Fei-Fei Department of Information Engineering Harbin Institute of Technology Harbin China Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana-Champaign IL USA

"Bag of words" models have enjoyed much attention and achieved good performances in recent studies of object categorization. In most of these works, local patches are modeled as basic building blocks of an image, analogous to words in text documents. In most previous works using the "bag of words" models (e.g. [4, 20, 7]), the local patches are assumed to be independent with each other. In this paper, we relax the independence assumption and model explicitly the inter-dependency of the local regions. Similarly to previous work , we represent images as a collection of patches, each of which belongs to a latent "theme" that is shared across images as well as categories. We learn the theme distributions and patch distributions over the themes in a hierarchical structure [22]. In particular, we introduce a linkage structure over the latent themes to encode the dependencies of the patches. This structure enforces the semantic connections among the patches by facilitating better clustering of the themes. As a result, our models for object categories tend to be more discriminative than the ones obtained under the independent patch assumption. We show highly competitive categorization results on both the Caltech 4 and Caltech 101 object category datasets. By examining the distributions of the latent themes for each object category, we construct an object taxonomy using the 101 object classes from the Caltech 101 datasets.

关键词： Wheels computer vision Couplings Taxonomy Object recognition Humans Robots Robustness Shape Solid modeling

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An Integrated Segmentation and Classification Approach Applied to Multiple Sclerosis Analysis

An Integrated Segmentation and Classification Approach Appli...

引用

conference on computer vision and pattern recognition (CVPR)

作者： A. Akselrod-Ballin M. Galun R. Basri A. Brandt M.J. Gomori M. Filippi P. Valsasina Dept. of Computer Science and Applied Math Weizmann Institute of Science Rehovot Israel Dept. of Radiology Hadassah University Hospital Jerusalem Israel Neuroimaging Research Unit Hospital San Raffaele Milan Italy

We present a novel multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility in detecting multiple sclerosis lesions in 3D MRI data. Our method uses segmentation to obtain a hierarchical decomposition of a multi-channel, anisotropic MRI scan. It then produces a rich set of features describing the segments in terms of intensity, shape, location, and neighborhood relations. These features are then fed into a decision tree-based classifier, trained with data labeled by experts, enabling the detection of lesions in all scales. Unlike common approaches that use voxel-by-voxel analysis, our system can utilize regional properties that are often important for characterizing abnormal brain structures. We provide experiments showing successful detections of lesions in both simulated and real MR images.

关键词： Multiple sclerosis Image segmentation Lesions Brain Magnetic resonance imaging Biomedical imaging Anisotropic magnetoresistance Shape Decision trees Classification tree analysis

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Image Matching Using Photometric Information

Image Matching Using Photometric Information

引用

conference on computer vision and pattern recognition (CVPR)

作者： M. Kolomenkin I. Shimshoni Electrical Engineering Department Technion-Israel Institute of Technology Haifa Israel Department of Management Information Systems Haifa University Haifa Israel

Image matching is an essential task in many computer vision applications. It is obvious that thorough utilization of all available information is critical for the success of matching algorithms. However most popular matching methods do not incorporate effectively photometric data. Some algorithms are based on geometric, color invariant features, thus completely neglecting available photometric information. Others assume that color does not differ significantly in the two images; that assumption may be wrong when the images are not taken at the same time, for example when a recently taken image is compared with a database. This paper introduces a method for using color information in image matching tasks. Initially the images are segmented using an off-the-shelf segmentation process (EDISON). No assumptions are made on the quality of the segmentation. Then the algorithm employs a model for natural illumination change to define the probability of two segments to originate from the same surface. When additional information is supplied (for example suspected corresponding point features in both images), the probabilities are updated. We show that the probabilities can easily be utilized in any existing image matching system. We propose a technique to make use of them in a SIFT-based algorithm. The technique’s capabilities are demonstrated on real images, where it causes a significant improvement in comparison with the original SIFT results in the percentage of correct matches found.

关键词： Image matching Photometry Image segmentation computer vision Lighting Image databases Management information systems Application software Spatial databases Layout

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Person Verification by Lip-Motion

Person Verification by Lip-Motion

引用

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

作者： M.I. Faraj J. Bigun School of Information Science Computer and Electrical Engineering (IDE) Halmstad University Halmstad Sweden

This paper describes a new motion based feature extraction technique for speaker recognition using orientation estimation in 2D manifolds. The motion is estimated by computing the components of the structure tensor from which normal flows are extracted. By projecting the 3D spatiotemporal data to 2-D planes we obtain projection coefficients which we use to evaluate the 3-D orientations of brightness patterns in TV like 2D image sequences. This corresponds to the solutions of simple matrix eigenvalue problems in 2D, affording increased computational efficiency. An implementation based on joint lip movements and speech is presented along with experiments which confirm the theory, exhibiting a recognition rate of 98% on the publicly available XM2VTS database.

关键词： Motion estimation Feature extraction Speaker recognition Tensile stress Data mining Spatiotemporal phenomena Two dimensional displays Brightness TV Image sequences

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Robust Real-Time Face Pose and Facial Expression Recovery

Robust Real-Time Face Pose and Facial Expression Recovery

引用

conference on computer vision and pattern recognition (CVPR)

作者： Zhiwei Zhu Qiang Ji Department of ECSE Rensselaer Polytechnic Institute Troy NY USA Sarnoff Corporation USA

Face motion is the sum of rigid motion related with face pose and non-rigid motion related with facial expression. Both motions are coupled in the captured image so that they can not be easily recovered from the image directly. In this paper, a novel technique is proposed to recover 3D face pose and facial expression simultaneously from a monocular video sequence in real time. First, twenty-eight salient facial features are detected and tracked robustly under various face orientations and facial expressions. Second, after modelling the coupling between face pose and facial expression in the 2D image as a nonlinear function, a normalized SVD (N-SVD) decomposition technique is proposed to recover the pose and expression parameters analytically. A nonlinear technique is subsequently utilized to refine the solution obtained from the N-SVD technique by imposing the orthonormality constraint on the pose parameters. Compared to the original SVD technique proposed in [1], which is very sensitive to the image noise and numerically unstable in practice, the proposed method can recover the face pose and facial expression robustly and accurately. Finally, the performance of the proposed technique is evaluated in the experiments using both synthetic and real image sequences.

关键词： Robustness Facial animation Motion estimation Face detection Cameras Image analysis Head Human computer interaction Face recognition Video sequences

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