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Perceptual completion of occluded surfaces

Perceptual completion of occluded surfaces

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Williams Hanson NEC Research Institute Inc. Princeton NJ USA Department of Computer Science University of Massachusetts Amherst MA USA

Researchers in computer vision have primarily studied the problem of visual reconstruction of environmental structure that is plainly visible. In this paper, the conventional goals of visual reconstruction are generalized to include both visible and occluded forward facing surfaces. This larger fraction of the environment is termed the anterior surfaces. In this paper, we show that the boundaries of the anterior surfaces can be represented in viewer-centered coordinates as a labeled knot diagram. Where boundaries are not occluded and where surface reflectance is distinct from that of the background, boundaries will be marked by image contours. However, where boundaries are occluded, or where surface reflectance matches background reflectance, there will be no detectable luminance change in the image. Deducing the complete image trace of the boundaries of the anterior surfaces under these circumstances is termed the figural completion problem. The second half of this paper describes a computational theory of figural completion. A working model is demonstrated on a variety of illusory contour displays. The experimental system employs a two stage process of completion hypothesis and combinatorial optimization. The labeling scheme is enforced by integer linear inequalities so that the optimal feasible solution of an integer linear program defines a typologically valid surface organization.< >

关键词： Machine vision Image reconstruction Optical reflection Integer programming Linear programming

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On the relative brightness of specular and diffuse reflection

On the relative brightness of specular and diffuse reflectio...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Wolff Computer Vision Laboratory Department of Computer Science Johns Hopkins University Baltimore MD USA

Inhomogeneous dielectric surfaces exhibit both diffuse and specular reflection components. While various reflection models have been proposed for both of these components, the prediction of the relative strengths of these components in computer vision and computer graphics has so far not had a strong physical motivation. We propose in this paper a reflectance model for combined diffuse and specular reflection from dielectric materials which involves purely physical parameters (i.e., no ad hoc weighting of specular and diffuse components). This reflectance model is used to predict the relative strength of diffuse and specular reflection components in terms of imaging geometry, dielectric surface parameters, and, solid angular extent of incident light. We derive lower bounds on the contrast ratio between a specularity and surrounding diffuse reflecting regions. These can be used effectively to rule out highly contrasting diffuse reflecting regions being misidentified as specularities under a number of conditions which can significantly aid intensity-based specularity detection methods, and in turn image understanding. The theoretical developments in this paper can be used to predict the photometric dynamic range of illuminated objects which can be essential to inspection methods in machine vision. The developments in this paper can also be used in computer graphics for the physically precise rendering of the relative strengths of specular and diffuse reflection from inhomogeneous dielectrics.< >

关键词： computer graphics Machine vision Inspection

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Automatic selection of tuning parameters for feature extraction sequences

Automatic selection of tuning parameters for feature extract...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Ramesh Haralick Xining Zhang Nadadur Thornton Department of EE FT-10 University of Washington Seattle WA USA Washington University in Saint Louis Saint Louis MO US Dept. of Electr. Eng. Washington Univ. Seattle WA USA

computer vision algorithms are composed of different sub-algorithms often applied in sequence. Previous work on performance characterization illustrated how random perturbation models can be setup at various stages of an algorithm sequence for the input and output data. In this paper we address the issue of how one could utilize these random perturbation models in order to automate the selection of free parameters used in an algorithm sequence. We consider an operation sequence that involves edge finding, linking, corner finding and matching. Appropriate prior distributions for the parameters that describe the graytone/geometric characteristics of the image features are specified and validated by using an annotation process. The annotation process involves the manual specification (outlining) of the geometry and spatial extent of the image features. Statistics are gathered for parameters describing features of interest and non-interest (clutter features). The appropriate prior distributions are used to derive the theoretical expressions for feature detector performance over a given image population. These performance measures are then optimized to determine the tuning parameters for the feature detector(s).< >

关键词： Feature extraction Machine vision

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A visual-motion fixation invariant

A visual-motion fixation invariant

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Raviv Ozery Robotics Center and Department of Electrical Engineering Florida Atlantic University Boca Raton FL USA Robot Systems Division National Institute for Standards and Technology Gaithersburg MD USA Florida Atlantic University Boca Raton FL US Robotics Center Florida Atlantic Univ. Boca Raton FL USA

The paper deals with a visual-motion fixation invariant. We show that during fixation there is a measurable nonlinear function of optical flow that produces the same value for all points of a stationary environment, regardless of the 3D shape of the environment. During fixated camera motion relative to a rigid object, e.g., a stationary environment, the projection of the fixated point remains (by definition) at the same location in the image, and all other points located on the 3D rigid object can only rotate relative to the 3D fixation point. This rotation rate of the points is invariant for all points that lie on the particular environment, and it is measurable from a sequence of images. This new invariant is obtained from a set of monocular images, and is expressed explicitly as a closed form solution. We show how to extract this invariant analytically from a sequence of images using optical flow information, and we present results obtained from real data experiments.< >

关键词： Image motion analysis Robots, vision systems Cameras Image sequence analysis

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Principal component analysis with missing data and its application to object modeling

Principal component analysis with missing data and its appli...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Heung-Yeung Shum Ikeuchi Reddy The Robotics Institute Carnegie Mellon University USA

Observation-based modeling can reduce the cost and effort of model constructions for tasks such as virtual reality environment. Object modeling from a sequence of range images has been formulated as a problem of principal component analysis with missing data (PCAMD), which can be generalized as a weighted least square (WLS) minimization problem. After all visible regions appeared over the whole sequence are segmented and tracked, a normal measurement matrix of surface normals and a distance measurement matrix of normal distances to the origin are constructed respectively. These two measurement matrices, with possibly many missing elements due to occlusion and mismatching, enable us to formulate multiple view merging as a combination of two WLS problems. The solution to the first WLS problem, which employs the quaternion representation of the rotation matrix, yields surface normals and rotation matrices. Subsequently the normal distances and translation vectors are computed by solving the second WLS problem. Experiments using synthetic data and real range images show that our approach is robust against noise and mismatch because it produces a statistically optimal object model by making use of redundancy from multiple views. A toy house model from a sequence of real range images is presented.< >

关键词： Least-mean-square methods Minimization methods Matrices Virtual reality Image segmentation Machine vision Modeling

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Tracking of tubular objects for scientific applications

Tracking of tubular objects for scientific applications

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Parvin Peng Johnston Maestre Imaging Techiologies Group Lawrence Berkeley Laboratory ICSD Inc. Berkeley CA USA E O Lawrence Berkeley National Laboratory Berkeley CA US Imaging Technol. Group Lawrence Berkeley Lab. CA USA Biological Structures Group Lawrence Berkeley Laboratory LSD Berkeley CA USA

We present a system for detection, tracking and representation of tubular objects in images. The uniqueness of the proposed system is twofold: at the macro level, the novelty of the system lies in the integration of object localization and tracking using geometric properties; at the micro level, is the use of high and low level constraints to model the detection and tracking subsystem. The underlying philosophy for object detection is to extract perceptually significant features from the pixel level image, and then use these high level cues to refine the precise boundaries. In the case of tubular objects, the perceptually significant features are anti-parallel line segments or, equivalently, their axis of symmetries. The axis of symmetry infers a coarse description of the object in terms of a bounding polygon. The polygon then provides the necessary boundary condition for the refinement process, which is based on dynamic programming. For tracking the object in a time sequence of images, the refined contour is then projected onto each consecutive frame. In addition, the system provides an axis of symmetry representation of object for subsequent scientific analysis.< >

关键词： Dynamic programming Object detection Machine vision

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Medium level scene representation using a VLSI smart hexagonal sensor with multiresolution edge extraction capability and scale space integration processing

Medium level scene representation using a VLSI smart hexagon...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Tremblay Savard Poussart Computer Vision and Digital Systems Laboratory Department of Electrical Engineering Laval University QUE Canada

This paper presents a sensing approach where photo-transduction, multi-resolution feature extraction, scale-space integration and edge tracking are performed on a mixed (digital-analog) VLSI architecture in order to generate medium-level scene description. The proposed system is mainly targeted for robot vision applications where feature description is preferred to a set of raw or raster 2D images and edge maps. The Multiport Access photo-Receptor (MAR) is a CMOS sensor and represents the main sensory part of this integrated image acquisition system. VLSI also provides means to integrate analog computing, digital controller and DSP co-processor modules which define a powerful sensory chip set for focal plane image processing. A current version of the MAR sensor which implements 256/spl times/256 pixels includes 16 analog spatial filters which simultaneously compute multiresolution edge maps. This unique 2D hexagonal smart sensor approach which performs up to 8.5/spl times/10/sup 9/ arithmetic Op/sec during the acquisition/filtering phase and 25/spl times/10/sup 9/ Logical Op/sec for scale-space integration allows high resolution image capability. It represents a significant improvement for passive sensory units in a compact assembly for computer vision applications.< >

关键词： Very-large-scale integration Image edge analysis Feature extraction Robots, vision systems Spatial filters CMOS integrated circuits Image sensors

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Scene understanding from propagation and consistency of polarization-based constraints

Scene understanding from propagation and consistency of pola...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Wolff Computer Vision Laboratory Department of Computer Science Johns Hopkins University Baltimore MD USA

We show how the more general capabilities of polarization vision can be used to significantly enhance the understanding of imaged scenes particularly at regions containing specular and mirror reflections, and occluding contours. Intensity-based methods are easily confounded by specular reflection. Specular mirror reflection of an object is indistinguishable from the object itself when using intensity and color, but is shown to be distinguishable when reflected polarization is analyzed. Polarization-based methods also enhance the identification of occluding contour edges, and regions that are in the vicinity of occluding contour edges. In past work local polarization constraints have been shown to accurately label specularities and occluding contours in simple scenes. In more complicated scenes under general conditions local polarization constraints are usually not sufficient to produce an accurate labeling of these phenomena. The main new idea presented in this paper is to extract much more additional information by enforcing physical consistency between neighboring local polarization constraints and propagating these constraints across pixel edges and regions with significant partial polarization. Initial labeling of pixels is produced from local polarization constraints at edges. We present well-defined physically motivated rules for relabeling pixels where physical inconsistencies result between neighboring local polarization constraints. Propagation rules allow physically consistent labeling of regions of significant partial polarization, and a refinement rule allows some more detailed labeling of edges. We include the previously unstudied case of specular reflection at/near occluding contours. In all 10 edge and region labels are generated. Experimental results on a complex scene is presented demonstrating the vast amount of information that can be extracted from these new physical principles of polarization vision.< >

关键词： Polarization Machine vision Image edge analysis Image region analysis

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Artificial Intelligence Applications and Innovations 1

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丛书名： IFIP Advances in Information and Communication Technology

1000年

作者： Harris Papadopoulos Andreas S. Andreou Lazaros Iliadis Ilias Maglogiannis

ISBN: (数字)9783642411427

ISBN: (纸本)9783642411410;9783662525128

This book constitutes the refereed proceedings of the 9th IFIP WG 12.5 International conference on Artificial Intelligence Applications and Innovations, AIAI 2013, held in Paphos, Cyprus, in September/October 2013. The 26 revised full papers presented together with a keynote speech at the main event and 44 papers of 8 collocated workshops were carefully reviewed and selected for inclusion in the volume. The papers of the main event are organized in topical sections on data mining, medical informatics and biomedical engineering, problem solving and scheduling, modeling and decision support systems, robotics, and intelligent signal and image processing.

关键词： Artificial Intelligence pattern recognition Data Mining and Knowledge Discovery Image Processing and computer vision computers and Education Information Systems Applications (incl. Internet)

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Image and Video Technology – PSIVT 2013 workshops 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Fay Huang Akihiro Sugimoto

ISBN: (数字)9783642539268

ISBN: (纸本)9783642539251

This book constitutes the thoroughly refereed post-conference proceedings of the four workshops on Photographic Aesthetics and Non-Photorealistic Rendering (PAESNPR13), Geometric Properties from Incomplete Data (GPID), Quality Assessment and Control by Image and Video Analysis (QACIVA) and Geometric Computation for computer vision (GCCV2013), held in conjunction with the 6th Pacific-Rim Symposium on Image and Video Technology (PSIVT) in Guanajuato, Mexico during October 28-November 1, 2013. The 38 revised full papers presented were carefully selected from numerous submissions and cover all aspects of Imaging and Graphics Hardware and Visualization, Image/Video Coding and Transmission; Processing and Analysis; Retrieval and Scene Understanding, but also Applications of Image and Video Technology, Biomedical Image Processing and Analysis, Biometrics and Image Forensics, Computational Photography and Arts, computer and Robot vision, pattern recognition and Video Surveillance.

关键词： Image Processing and computer vision Artificial Intelligence pattern recognition computer Graphics Algorithm Analysis and Problem Complexity Information Systems Applications (incl. Internet)

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