OpenRaiser/Intern-Atlas huggingface dataset:
Robust object recognition based on implicit algebraic curves and surfaces
Authors: Daniel Keren, Jayashree Subrahmonia, David B. Cooper
Venue: CVPR
Year: 1992

Two problems pertinent to using implicit higher degree polynomials in real-world robust systems are dealt with: (1) characterization and fitting algorithms for the subset of these algebraic curves and surfaces that is bounded and exists largely in the vicinity of the data; (2) a Mahalanobis distance for comparing the coefficients of two polynomials, to determine whether the curves or surfaces that they represent are close over a specified region. These tools make practical use of geometric invariants for determining whether one implicit polynomial curve or surface is a rotation, translation, or an affine transformation of another. The approach is ideally suited to smooth curves and smooth curved surfaces that do not have detectable features.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Refinement of noisy correspondence using feedback from 3D motion
Authors: Yong C. Kim, Keith Price
Venue: CVPR
Year: 1992

In automated feature-based motion analysis of multiple frames, correspondence data are usually noisy and fragmented. A technique that gradually refines the initial noisy correspondence data and links fragments of a single trajectory using feedback from 3D motion estimation is presented. First, 3D motion parameters are estimated using the initial correspondence data. Then, each noisy trajectory is partitioned into subsets of points, each of which conforms to the estimated motion. The best set is used as the input to the next motion estimation. This process is repeated, and the gaps in the refined correspondence data are filled by guidance from the predicted motion. Test results for a standard real image sequence are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Edge detection in range images through morphological residue analysis
Authors: Raghu Krishnapuram, Sundeep Gupta
Venue: CVPR
Year: 1992

Two morphological methods for edge detection in range images are proposed. The first method uses the opening and closing residues of structuring elements in orthogonal directions to detect roof and crease edges, and is essentially a morphological implementation of residue analysis techniques. The more general second method is based on a morphological version of the first derivative operator. This method utilizes dilation and erosion residues of structuring elements at different scales to reliably extract step edges along with roof edges and crease edges, and to classify each pixel as belonging to eight possible structure types: positive roof, negative roof, positive crease, negative crease, top of step, base of step, ramp, and constant surface. This method may be thought of as a morphological multiscale method.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
3D model acquisition from monocular image sequences
Authors: Rakesh Kumar 0001, Harpreet S. Sawhney, Allen R. Hanson
Venue: CVPR
Year: 1992

Automatic building 3D models of objects and scenes from a sequence of 2D monocular images is approached by first building a partial model (possibly noisy) and then extending and refining it. The initial model is built by tracking and reconstructing shallow structures over a sequence of images using the constraint of affine trackability. This model is subsequently used to compute the pose that relates the model coordinate system and the camera coordinate system of the image frames in the sequence. The unmodeled 3D features (those not recovered by the shallow structure reconstruction) are tracked over the image sequence and their 3D locations recovered by a pseudotriangulation process. The triangulation process is also used to make new 3D measurements of the initial model points. These measurements are then fused with the previous estimates to refine the set of initial model points.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Recovering shape by purposive viewpoint adjustment
Authors: Kiriakos N. Kutulakos, Charles R. Dyer
Venue: CVPR
Year: 1992

An approach for recovering surface shape from the occluding contour using an active (i.e., moving) observer is presented. It is based on a relationship between the geometries of a surface in a scene and its occluding contour: If the viewing direction of the observer is along a principal direction for a surface point whose projection is on the contour, surface shape (i.e., curvature) at the surface point can be recovered from the contour. An observer that purposefully changes viewpoint in order to achieve a well-defined geometric relationship with respect to a 3D shape prior to its recognition is used. It is shown that there is a simple and efficient viewing strategy that allows the observer to align the viewing direction with one of the two principal directions for a point on the surface. Experimental results demonstrate that the method can be easily implemented and can provide reliable shape information.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Qualitative shape from active shading
Authors: Michael S. Langer, Steven W. Zucker
Venue: CVPR
Year: 1992

It is shown how to actively compute qualitative shape properties of a surface directly from image intensities without first quantitatively reconstructing the surface. The approach diverges from classical active shape-from-shading in that two different types of lighting conditions (a diffuse source and a point source) are used, rather than two instances of a single type (a point source). There is no attempt to compute a dense depth map of the surface. Rather, the presence of certain qualitative geometric features is detected. In particular, a shape property, surface aperture, is introduced, and it is shown that under diffuse lighting there is typically a spatial correspondence between the minima of surface aperture and the minima of image intensity. Thus, the minima in surface aperture can be located. Different possible causes of the aperture minima can subsequently be distinguished by actively illuminating the surface with a point source positioned in the viewing direction.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Multiple motions from instantaneous frequency
Authors: Keith Langley, David J. Fleet, Tim J. Atherton
Venue: CVPR
Year: 1992

The measurement of multiple velocities using phase-based methods is discussed. In particular, phase gradients (instantaneous frequency) from different bandpass channels (quadrature filter outputs) are used to estimate multiple image velocities in a single neighborhood. The approach is similar to that of M. Shizawa and K. Mase (1990) in which nth-order differential operators are required to compute n simultaneous velocity estimates. However, to use instantaneous frequency, the output of each channel must be differentiated only once.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Computing the view orientations of random projections of asymmetric objects
Authors: Peter D. Lauren, N. Nandhakumar
Venue: CVPR
Year: 1992

A method for determining the relative view orientation of randomly acquired projections of asymmetric objects is described. It extends the projection slice theorem by determining the relative orientation of projections by the location of lines of intersection among the Fourier transforms of the projections in 3D Fourier space. The complete algorithm is described, and its efficacy is demonstrated using real data.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Shape reconstruction from photometric stereo
Authors: Kyoung Mu Lee, C.-C. Jay Kuo
Venue: CVPR
Year: 1992

Two iterative algorithms for shape reconstruction based on multiple images taken under different lighting conditions, known as photometric stereo, are proposed. It is shown that single-image shape-from-shading (SFS) algorithms have an inherent problem, i.e., the accuracy of the reconstructed surface height is related to the slope of the reflectance map function defined on the gradient space. This observation motivates the authors to generalize the single-image SFS algorithm to two photometric stereo SFS algorithms aiming at more accurate surface reconstruction. The two algorithms directly determine the surface height by minimizing a quadratic cost functional, which is defined to be the square of the brightness error obtained from each individual image in a parallel or cascade manner. The optimal illumination condition that leads to best shape reconstruction is examined.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Handwritten numeral recognition based on hierarchically self-organizing learning networks with spatio-temporal pattern representation
Authors: Sukhan Lee 0001, Jack C. Pan
Venue: CVPR
Year: 1992

An approach for tracing, representation, and recognition of a handwritten numeral in an offline environment is presented. A 2D spatial representation of a numeral is first transformed into a 3D spatiotemporal representation by identifying the tracing sequence based on a set of heuristic rules acting as transformation operators. Given the dynamic information of the tracing sequence, a multiresolution critical-point segmentation method is proposed to extract local feature points, at varying degrees of scale and coarseness. A neural network architecture, the hierarchically self-organizing learning (HSOL) network (S. Lee, J.C. Pan, 1989), especially for handwritten numeral recognition, is presented. Experimental results based on a bidirectional HSOL network indicated that the method is robust in terms of variations, deformations, and corruption, achieving about 99% recognition rate for the test patterns.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
3 D shape and light source location from depth and reflectance
Authors: Todd A. Mancini, Lawrence B. Wolff
Venue: CVPR
Year: 1992

A methodology for accurate determination of surface normals and light source location from depth and reflectance data is introduced. Estimation of local surface orientation using depth data alone from range finders with standard depth errors can produce significant error, while shape-from-shading using reflectance data alone produces approximate surface orientation results that are highly dependent on the correct initial surface orientation estimates and regularization parameters. Combining these two sources of information gives vastly more accurate surface orientation estimates under general conditions than either one alone, and can also provide better knowledge of local curvature. Novel iterative methods that enforce satisfaction of the image irradiance equation and surface integrability without using regularization are proposed. These iterative methods work when the light source is any finite distance from the object, producing variable incident light orientation over the object.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A feature based approach to face recognition
Authors: B. S. Manjunath, Rama Chellappa, Christoph von der Malsburg
Venue: CVPR
Year: 1992

A feature-based approach to face recognition in which the features are derived from the intensity data without assuming any knowledge of the face structure is presented. The feature extraction model is biologically motivated, and the locations of the features often correspond to salient facial features such as the eyes, nose, etc. Topological graphs are used to represent relations between features, and a simple deterministic graph-matching scheme that exploits the basic structure is used to recognize familiar faces from a database. Each of the stages in the system can be fully implemented in parallel to achieve real-time recognition. Experimental results for a 128*128 image with very little noise are evaluated.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Multi-primitive hierarchical (MPH) stereo system
Authors: Suresh B. Marapane, Mohan M. Trivedi
Venue: CVPR
Year: 1992

A computational framework for an accurate, robust, and efficient stereo approach is developed. Most of the deficiencies prevailing in current computational models of stereo can be attributed to their use of a single, typically edge-element-based, primitive for stereo analysis and to their use of a single-level control strategy. The multi-primitive hierarchical (MPH) framework for stereo analysis presented is directed toward overcoming these deficiencies. In the MPH model, stereo analysis is performed in multiple stages, incorporating multiple primitives and utilizing a hierarchical control strategy. The higher levels of the hierarchical system are based on primitives containing more semantic information, and the results of stereo analysis at higher levels are used for guidance at the lower levels. It is shown that such a stereo system is superior to a single-level, single-primitive system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Toward stochastic modeling of obstacle detectability in passive stereo range imagery
Authors: Larry H. Matthies
Venue: CVPR
Year: 1992

To design high-performance obstacle detection systems for semi-autonomous navigation, it will be necessary to characterize the performance of obstacle detection sensors in quantitative, statistical terms and to develop design methodologies that relate task requirements (e.g., vehicle speed) to sensor system parameters (e.g., image resolution). Steps to be taken to realize such a methodology are outlined. For the specific case of obstacle detection with passive stereo range imagery, the development of the statistical models needed for the methodology is begun, and experimental results for outdoor images of a gravel road, which test the models empirically, are presented. The experimental results show sample error distributions for estimates of disparity and range, illustrate systematic errors caused by partial occlusion, and demonstrate that effective obstacle detection is achievable.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Hierarchical waveform matching: a new feature-based stereo technique
Authors: David M. McKeown Jr., Yuan C. Hsieh
Venue: CVPR
Year: 1992

A feature-based stereo matching system that is based on an algorithm for one-dimensional waveform matching is described. It is intended for use in automated cartography, to generate an accurate three-dimensional model of man-made structures and natural terrain. Each epipolar line in the stereo pair is represented as a one-dimensional intensity waveform. The waveform is described as a collection of features, such as peaks and valleys, and represented across a set of hierarchical levels, computed by approximation from the original waveform. These features are matched using an evaluation function that factors similarity of waveform shape, intensity, and symbolic feature description. Waveform matches at coarse resolution are used to constrain matches at finer levels. Intra/inter-scanline corrections are applied and the actual position of the stereo match is adjusted by using the gradient representation of the original waveform. Some representative results are presented for a complex urban scene.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Refinement of disparity estimates through the fusion of monocular image segmentations
Authors: David M. McKeown Jr., Frederic P. Perlant
Venue: CVPR
Year: 1992

The authors examine how estimates of three-dimensional scene structure, as encoded in a scene disparity map, can be improved by the analysis of the original monocular imagery. They describe the utilization of surface illumination information provided by the segmentation of the monocular image into fine surface patches of nearly homogeneous intensity to remove mismatches generated during stereo matching. These patches are used to guide a statistical analysis of the disparity map based on the assumption that such patches correspond closely with physical surfaces in the scene. Such a technique is quite independent of whether the initial disparity map was generated by automated area-based or feature-based stereo matching. Refinement results on complex urban scenes containing various man-made and natural features are presented, and the improvements due to monocular fusion with a set of different region-based image segmentations are demonstrated.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Robust consensus based edge detection
Authors: Doron Mintz
Venue: CVPR
Year: 1992

A robust algorithm for edge detection is presented. The algorithm detects both roof- and step-type edges. A pixel is declared as an edge pixel if there is a consensus between different processes that try to determine if the pixel lies on a discontinuity. Robust methods are used to estimate local fits to windows in the pixel's neighborhood and accumulate votes from each fit. The use of robust estimators allows the transformation of any window possibly containing a discontinuity to a binary window containing a step edge in the location of the discontinuity. Conventional methods are used to detect this step edge.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Analysis of the least median of squares estimator for computer vision applications
Authors: Doron Mintz, Peter Meer, Azriel Rosenfeld
Venue: CVPR
Year: 1992

The robust least-median-of-squares (LMedS) estimator, which can recover a model representing only half the data points, was recently introduced in computer vision. Image data, however, is usually also corrupted by a zero-mean random process (noise) accounting for the measurement uncertainties. It is shown that in the presence of significant noise, LMedS loses its high breakdown point property. A different, two-stage approach in which the uncertainty due to noise is reduced before applying the simplest LMedS procedure is proposed. The superior performance of the technique is proved by comparative graphs.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
An information theoretic robust sequential procedure for surface model order selection in noisy range data
Authors: Muhammad J. Mirza, Kim L. Boyer
Venue: CVPR
Year: 1992

Modeling of the unknown surface, a key first step in the perception of surfaces in range images using the function approximation approach, is considered. Akaike's entropy-based information criterion (AIC) is a simple but powerful tool for choosing the best fitting model among several competing models. However, the AIC presupposes a fixed data set and a normality assumption on the error's distribution. The AIC is extended to a t-distribution noise model, which more realistically represents anomalies in the data such as outliers and quantization errors. This criterion is modified to be used with a robust sequential algorithm to accommodate the variable data size resulting from fitting different models. The modified criterion is applied to real range data, and its performance is compared with that of AIC and Consistent AIC.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Visual inspection of machined parts
Authors: Bharath R. Modayur, Linda G. Shapiro, Robert M. Haralick
Venue: CVPR
Year: 1992

A CAD-model-based machine vision system for dimensional inspection of machine parts is described, with emphasis on the theory behind the system. The original contributions of this work are: (1) the use of precise definitions of geometric tolerances suitable for use in image processing, (2) the development of measurement algorithms corresponding directly to these definitions, (3) the derivation of the uncertainties in the measurement tasks, and (4) the use of this uncertainty information in the decision-making process. Initial experimental results have verified the uncertainty derivations statistically and proved that the error probabilities obtained by propagating uncertainties are lower than those obtainable without uncertainty propagation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
From partial derivatives of 3-D density images to ridge lines
Authors: Olivier Monga, Serge Benayoun, Olivier D. Faugeras
Venue: CVPR
Year: 1992

Three-dimensional edge detection in voxel images is used to locate points corresponding to surfaces of 3-D structures, and the local geometry of these surfaces is characterized in order to extract points or lines which may be used by registration and tracking procedures. Typically, second-order differential characteristics of the surfaces must be calculated. To avoid the problem of establishing links between 3-D edge detection and local surface approximation it is proposed to compute the curvatures at locations designated as edge points, using the partial derivatives of the image directly. By assuming that the surface is defined locally by an iso-intensity-contour, it is possible to calculate directly the curvatures and characterize the local curvature extrema (ridge points) from the first, second, and third derivatives of the gray-level function. These partial derivatives can be computed using the operators of the edge detection. Experimental results obtained using real X-ray scanner data are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Towards a general framework for feature extraction
Authors: Theo Moons, Eric J. Pauwels, Luc Van Gool, André Oosterlinck
Venue: CVPR
Year: 1992

It is shown how object recognition and optical flow can be captured within a single framework. These examples have been selected because they illustrate two complementary problems which can be tackled using the same unified approach based on Lie theory. The object recognition work referred to is based on the extraction of shape invariants and has been reported elsewhere. The present study focuses on using the same framework for the calculation of the optical flow. Besides the introduction of some new methods, it is shown that several well-known schemes can be derived following the same principles.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Nonlinear multiscale filtering using mathematical morphology
Authors: Aldo W. Morales, Raj Acharya
Venue: CVPR
Year: 1992

A multiscale filtering scheme based on the three Matheron axioms for morphological openings is developed. It is shown that opening a signal with a gray scale operator does not introduce additional zero-crossings as one moves to coarser scales. Within this framework, the problem of choosing an appropriate structuring element is studied. In order to obtain a measure of the performance of different structuring elements, the statistical properties of gray scale opening are studied, using a powerful tool in mathematical morphology, namely, basis functions.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
The image understanding environment program
Authors: Joseph L. Mundy, Thomas O. Binford, Terrance E. Boult, Allen R. Hanson, J. Ross Beveridge, Robert M. Haralick, Visvanathan Ramesh, Charles A. Kohl, Daryl T. Lawton, Doug Morgan, Keith Price, Tom Strat
Venue: CVPR
Year: 1992

The Image Understanding Environment (IUE) project is a five-year program, sponsored by ARPA, to develop a common software environment for the development of algorithms and application systems. This article reviews the history of the project and provides an overview of the IUE design.