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Video-rate stereo depth measurement on programmable hardware

Video-rate stereo depth measurement on programmable hardware

引用

conference on computer Vision and pattern recognition (CVPR)

作者： A. Darabiha J. Rose J.W. Maclean Department of Electrical and Computer Engineering University of Toronto Italy

This paper describes the implementation of a stereo depth measurement algorithm in hardware on field programmable gate arrays (FPGAs). This system generates 8 bit sub-pixel disparities on 256 by 360 pixel images at video rate (30 frames/sec). The algorithm implemented is a multi-resolution, multi-orientation phase-based technique called local weighted phase-correlation (Fleet, 1994). Hardware implementation speeds up the performance more than 300 times that of the same algorithm running in software. In this paper, we describe the programmable hardware platform, the base stereo vision algorithm and the design of the hardware. We include various trade-offs required to make the hardware small enough to fit on our system and fast enough to work at video rate. We also show sample outputs from the functioning hardware. Although this paper is specifically focused on phase-based stereo vision FPGA realizations, most of the design issues are common to other DSP and vision applications.

关键词： Hardware Field programmable gate arrays Table lookup Stereo vision Random access memory Circuits image processing Digital signal processing image edge detection computer society

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Document image enhancement using directional wavelet

Document image enhancement using directional wavelet

引用

conference on computer Vision and pattern recognition (CVPR)

作者： Qian Wang Tao Xia Lida Li Chew Lim Tan Dept. of Comput. Sci. Nat. Univ. of Singapore Singapore Centre for Wavelets Approximation and Information Processing Department of Mathematics National University of Singapore Singapore

ISBN: (纸本)0769519008

This paper proposes an algorithm to clean up a large collection of historical handwritten documents kept up in the National Archives of Singapore. Due to the seepage of ink over long period of storage, the front page of each document has been severely marred by the reverse side writing. Earlier attempts have been made to match both sides of the page to identify the offending strokes originating from the back so as to eliminate them with the aid of a wavelet transform. Perfect matching, however, is difficult due to document skews, differing resolutions, inadvertently missing out reverse side and warped pages during image capture. An approach is now proposed to do away with double side mapping by using a directional wavelet transform that is able to distinguish the foreground and reverse side strokes much better than the conventional wavelet transform. Experiments have shown that the method indeed enhances the readability of each document significantly over after the directional wavelet operation without the need for mapping with its reverse side.

关键词： image enhancement Wavelet transforms Ink Writing image resolution computer science Information processing Mathematics Approximation algorithms Background noise

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Shedding light on the weather

Shedding light on the weather

引用

conference on computer Vision and pattern recognition (CVPR)

作者： S.G. Narasimhan S.K. Nayar Computer Science Department Columbia University NY USA

Virtually all methods in image processing.and computer vision, for removing weather effects from images, assume single scattering of light by particles in the atmosphere. In reality, multiple scattering effects are significant. A common manifestation of multiple scattering is the appearance of glows around light sources in bad weather. Modeling multiple scattering is critical to understanding the complex effects of weather on images, and hence essential for improving the performance of outdoor vision systems. We develop a new physics-based model for the multiple scattering of light rays as they travel from a source to an observer. This model is valid for various weather conditions including fog, haze, mist and rain. Our model enables us to recover from a single image the shapes and depths of sources in the scene. In addition, the weather condition and the visibility of the atmosphere can be estimated. These quantities can, in turn, be used to remove the glows of sources to obtain a clear picture of the scene. Based on these results, we demonstrate that a camera observing a distant source can serve as a "visual weather meter". The model and techniques described in this paper can also be used to analyze scattering in other media, such as fluids and tissues. Therefore, in addition to vision in bad weather, our work has implications for medical and underwater imaging.

关键词： Light scattering Particle scattering Atmospheric modeling Atmosphere Layout image processing computer vision Light sources Machine vision Rain

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Independent component analysis in a facial local residue space

Independent component analysis in a facial local residue spa...

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conference on computer Vision and pattern recognition (CVPR)

作者： Tae-Kyun Kim Hyunwoo Kim Wonjun Hwang Seok-Cheol Kee J. Kittler Centre for Vision Speech and Signal Processing University of Surrey UK Human Computer Interaction Laboratory Samsung Advanced Institute of Technology South Korea

In this paper, we propose an ICA (Independent Component Analysis) based face recognition algorithm, which is robust to illumination and pose variation. Generally, it is well known that the first few eigenfaces represent illumination variation rather than identity. Most PCA (Principal Component Analysis)-based methods have overcome illumination variation by discarding the projection to a few leading eigenfaces. The space spanned after removing a few leading eigenfaces is called the "residual face space". We found that ICA in the residual face space provides more efficient encoding in terms of redundancy reduction and robustness to pose variation as well as illumination variation, owing to its ability to represent non-Gaussian statistics. Moreover, a face image is separated into several facial components, local spaces, and each local space is represented by the ICA bases (independent components) of its corresponding residual space. The statistical models of face images in local spaces are relatively simple and facilitate classification by a linear encoding. Various experimental results show that the accuracy of face recognition is significantly improved by the proposed method under large illumination and pose variations.

关键词： Independent component analysis Principal component analysis Face recognition Lighting Statistics image databases Face detection Space technology Speech analysis Signal processing.algorithms

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Constructing 3D city models by merging ground-based and airborne views

Constructing 3D city models by merging ground-based and airb...

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conference on computer Vision and pattern recognition (CVPR)

作者： C. Frueh A. Zakhor Video and Image Processing Laboratory University of California Berkeley USA

In this paper, we present a fast approach to automated generation of textured 3D city models with both high details at ground level, and complete coverage for bird's-eye view. A close-range facade model is acquired at the ground level by driving a vehicle equipped with laser scanners and a digital camera under normal traffic conditions on public roads; a far-range Digital Surface Map (DSM), containing complementary roof and terrain shape, is created from airborne laser scans, then triangulated, and finally texture mapped with aerial imagery. The facade models are first registered with respect to the DSM by using Monte-Carlo-Localization, and then merged with the DSM by removing redundant parts and filling gaps. The developed algorithms are evaluated on a data set acquired in downtown Berkeley.

关键词： Cities and towns Merging Laser modes Land vehicles Road vehicles Vehicle driving Digital cameras Traffic control Surface texture Surface emitting lasers

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Hue fields and color curvatures: a perceptual organization approach to color image denoising

Hue fields and color curvatures: a perceptual organization a...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： O. Ben-Shahar S.W. Zucker Department of Computer Science Yale University New Heaven CT USA Department of Computer Science and Electrical Engineering Yale University New Heaven CT USA

The denoising of color images is an increasingly studied problem whose state-of-the-art solutions employ a variety of diffusion schemes. Specifying the correct diffusion is difficult, however, in part because of the subtleties of color interactions. We address this difficulty by proposing a perceptual organization approach to color denoising based on the principle of good continuation. We exploit the periodic chromatic (hue) component of the color in its representation as a frame field. We derive two hue curvatures and use them to construct a local model for the behavior of the color, which in turn specifies consistency constraints between nearby color measurements. These constraints are then used to replace noisy pixels by examining their spatial context. Such a contextual analysis (combined with standard methods to handle the scalar channels, saturation and lightness), results in a robust noise removal process that preserves discontinuities, singularities, and fine chromatic structures, including those that diffusion processes are prone to distort. We demonstrate our approach on a variety of synthetic and natural images.

关键词： Color Noise reduction computer science Computed tomography Colored noise Psychology Noise robustness Diffusion processes computer vision image processing

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Spacetime stereo: a unifying framework for depth from triangulation

Spacetime stereo: a unifying framework for depth from triang...

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conference on computer Vision and pattern recognition (CVPR)

作者： J. Davis R. Ramamoorthi S. Rusinkiewicz Honda Research Institute USA Columbia University USA Princeton University USA

Depth from triangulation has traditionally been treated in a number of separate threads in the computer vision literature, with methods like stereo, laser scanning, and coded structured light considered separately. In this paper, we propose a common framework, spacetime stereo, which unifies many of these previous methods. Viewing specific techniques as special cases of this general framework leads to insights regarding the solutions to many of the traditional problems of individual techniques. Specifically, we discuss a number of innovative possible applications such as improved recovery of static scenes under variable illumination, spacetime stereo for moving objects, structured light and laser scanning with multiple simultaneous stripes or patterns, and laser scanning of shiny objects. To suggest the practical utility of the framework, we use it to analyze one of these applications: recovery of static scenes under variable, but uncontrolled, illumination. Based on our analysis, we show that methods derived from the spacetime stereo framework can be used to recover depth in situations in which existing methods perform poorly.

关键词： Stereo vision Layout Lighting Stereo image processing Yarn computer vision Computational geometry Performance analysis Orbital robotics Robot vision systems

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Visual hull alignment and refinement across time: a 3D reconstruction algorithm combining shape-from-silhouette with stereo

Visual hull alignment and refinement across time: a 3D recon...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： G.K.M. Cheung S. Baker T. Kanade Robotics Institute Carnegie Mellon University Pittsburgh PA USA

Visual hull (VH) construction from silhouette images is a popular method of shape estimation. The method, also known as shape-from-silhouette (SFS), is used in many applications such as non-invasive 3D model acquisition, obstacle avoidance, and more recently human motion tracking and analysis. One of the limitations of SFS, however, is that the approximated shape can be very coarse when there are only a few cameras. In this paper, we propose an algorithm to improve the shape approximation by combining multiple silhouette images captured across time. The improvement is achieved by first estimating the rigid motion between the visual hulls formed at different time instants (visual hull alignment) and then combining them (visual hull refinement) to get a tighter bound on the object's shape. Our algorithm first constructs a representation of the VHs called the bounding edge representation. Utilizing a fundamental property of visual hulls, which states that each bounding edge must touch the object at at least one point, we use multi-view stereo to extract points called colored surface points (CSP) on the surface of the object. These CSPs are then used in a 3D image alignment algorithm to find the 6 DOF rigid motion between two visual hulls. Once the rigid motion across time is known, all of the silhouette images are treated as being captured at the same time instant and the shape of the object is refined. We validate our algorithm on both synthetic and real data and compare it with space carving.

关键词： Reconstruction algorithms Shape Surface treatment Stereo image processing Humans Motion analysis Tracking image motion analysis Cameras Approximation algorithms

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Identifying painters from color profiles of skin patches in painting images

Identifying painters from color profiles of skin patches in ...

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ieee International conference on image processing

作者： I. Widjaja W.K. Leow Fang-Cheng Wu Dept. of Computer Science National University of Singapore Singapore Institute of Art Studies National Central University Taiwan Taiwan

Research on digital analysis of painting images has received very little attention. The exact nature of scientific methods seems to be antithesis of art. Nevertheless, several papers have proposed methods to bridge this gap and have obtained interesting results. In fact, some art theorists have pointed out the usefulness of specific quantifiable features in the paintings. This paper presents a method for identifying painters using color profiles of skin patches in painting images. Various color models for representing the color profiles were explored. Various implementations of multiclass support vector machine classfiiers were compared. We found that a weighted combination of several directed acyclic graph SVMs with Gaussian kernels gives the best classification performance.

关键词： Skin Painting Support vector machines Data mining pattern recognition Voting Interpolation Testing Computational Intelligence society Kernel

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Equivalence and efficiency of image alignment algorithms

Equivalence and efficiency of image alignment algorithms

引用

conference on computer Vision and pattern recognition

作者： Baker, S Matthews, I Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

ISBN: (纸本)0769512720

There are two major formulations of image alignment using gradient descent. The first estimates an additive increment to the parameters (the additive approach), the second an incremental warp (the compositional approach). We first prove that these two formulations are equivalent. A very efficient algorithm was recently proposed by Hager and Belhumeur using the additive approach that unfortunately can only be applied to a very restricted class of warps. We show that using the compositional approach an equally efficient algorithm (the inverse compositional algorithm) can be derived that can be applied to any set of warps which form a group. While most warps used in computer vision form groups, there are a certain warps that do not. Perhaps most notable is the set of piecewise affine warps used in Flexible Appearance Models (FAMs). We end this paper by extending the inverse compositional algorithm to apply to FAMs.

关键词： image processing

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