OpenRaiser/Intern-Atlas huggingface dataset:
An object-oriented approach to template guided visual inspection
Authors: Joseph L. Mundy, J. Alison Noble, Constantinos Marinos, Van-Duc Nguyen, Aaron Heller, J. Farley, A. T. Tran
Venue: CVPR
Year: 1992

The concepts and design issues that provide the basis for the I/sup 2/F (image interpretation foundations) system are described. The I/sup 2/F system combines object-oriented design for machine vision software and constraint-based geometric modeling into a flexible and effective system for automatic template-guided visual inspection. Object-oriented design for 2-D geometry-based image analysis is discussed, and results from processing experimental X-ray data are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Parameter estimation in MRF line process models
Authors: Sateesha G. Nadabar, Anil K. Jain 0001
Venue: CVPR
Year: 1992

A scheme for the estimation of the Markov random field (MRF) line process parameters that uses geometric CAD models of the objects in the scene is presented. The models are used to generate synthetic images of the objects from random viewpoints. The edge maps computed from the synthesized images are used as training samples to estimate the line process parameters using a least squares method. It is shown that this parameter estimation method is useful for detecting edges in range as well as intensity images.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Shape from focus system
Authors: Shree K. Nayar
Venue: CVPR
Year: 1992

A shape-from-focus method that uses different focus levels to obtain a sequence of object images is described. A sum-modified-Laplacian operator is developed to provide local measures of the quality of image focus. The operator is applied to the sequence of images of the object to determine a set of focus measures as each image point. A model is developed to describe the variation of focus measure values due to defocusing. This model is used by a depth estimation algorithm to interpolate focus measure values and obtain accurate depth estimates. A fully automated system that has been implemented using an optical microscope and tested on a variety of industrial samples is described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Simple direct computation of the FOE with confidence measures
Authors: Shahriar Negahdaripour, Vidyasagar Ganesan
Venue: CVPR
Year: 1992

A direct method is proposed for locating the focus of expansion, based on simple parallel computations in selected regions of the image; each is a circular patch around an estimated focus of expansion (FOE). Simple computations allow determining the direction from the estimated to the true 400FOE. The best estimate of the intersection of the so-called FOE constraint lines for each region gives the location of the FOE. Some analysis allows a confidence measure to be assigned to the information from each local region, in order to give more weighting to the most reliable data. Hence, the FOE can be located with more accuracy, even when the data from various local regions lack sufficient information.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Direct motion stereo for passive navigation
Authors: Shahriar Negahdaripour, Nagesh Kolagani, Brian Y. Hayashi
Venue: CVPR
Year: 1992

We address the problem of motion recovery for a head-eye system from stereo image sequences. Two types of motions, the translation of the vehicle and the panning motion of the head, are considered. We show how these motions and the depth map of the scene can be estimated directly from the measurements of image gradients and time derivatives in a sequence of stereo images. There is no need to estimate image motion, track a scene feature over time, or establish point correspondences in a stereo image pair. We present the results of various experiments with real scenes.
Generating connected skeletons for exact and approximate reconstruction
Authors: Wayne Niblack, Phillip B. Gibbons, David W. Capson
Venue: CVPR
Year: 1992

An algorithm for generating skeletons of objects in a binary image is described. The algorithm produces a well-centered skeleton with the same simple connectivity as the object, and it allows the object to be either exactly or approximately (to within a known, user-selectable error) reconstructed. Its connectivity and reconstructability properties can be rigorously proved. For approximate reconstruction, the skeleton can also be (almost always) thin and is insensitive to border noise without image prefiltering or skeleton post-pruning, while maintaining the precise error bounds for reconstruction. Because of these properties, its robustness to rotation, pleasing visual appearance, and flexibility, it is well suited for such applications as data compression, image analysis, character recognition, and circuit board inspection.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Voronoi skeletons: theory and applications
Authors: Robert L. Ogniewicz, Markus Ilg
Venue: CVPR
Year: 1992

A novel method of robust skeletonization based on the Voronoi diagram of boundary points, which is characterized by correct Euclidean metries and inherent preservation of connectivity, is presented. The regularization of the Voronoi medial axis (VMA) in the sense of H. Blum's (1967) prairie fire analogy is done by attributing to each component of the VMA a measure of prominence and stability. The resulting Voronoi skeletons appear largely invariant with respect to typical noise conditions in the image and geometric transformations. Hierarchical clustering of the skeleton branches, the so-called skeleton pyramid, leads to further simplification of the skeleton. Several applications demonstrate the suitability of the Voronoi skeleton to higher-order tasks such as object recognition.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Local reproducible smoothing without shrinkage
Authors: John Oliensis
Venue: CVPR
Year: 1992

A simple local smoothing filter is defined for curves or surfaces, combining the advantages of Gaussian smoothing and Fourier curve description. Unlike Gaussian filters, the filter described has no shrinkage problem. Repeated application of the filter does not yield a curve or surface smaller than the original but simply reproduces the approximate result that would have been obtained by a single application at the largest scale. Unlike Fourier description, the filter is local in space. The wavelet transform of Y. Meyer (1989) is also shown to have these properties.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Shape from texture using Markov random field models and stereo-windows
Authors: Maqbool A. S. Patel, Fernand S. Cohen
Venue: CVPR
Year: 1992

The problem of extracting the local shape information of a 3D textured surface from a single 2D image is addressed. The textured objects of interest are planar and developable surfaces that are viewed as originating by laying down a rubber planar sheet with a homogeneous parent texture on it onto the objects. The homogeneous planar parent texture is modeled by a stationary Gaussian Markov random field (GMRF). The probability density function of the projected planar parent texture is an explicit function of the parent GMRF parameters, the surface shape parameters, and the camera geometry. The surface shape parameter estimation is posed as a maximum-likelihood estimation problem. A stereo-windows concept is introduced to obtain a unique and consistent parent texture from the image data.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Recognition of motion from temporal texture
Authors: Ramprasad Polana, Randal C. Nelson
Venue: CVPR
Year: 1992

A method of visual motion recognition applicable to a range of naturally occurring motions that are characterized by spatial and temporal uniformity is described. The underlying motivation is the observation that, for objects that typically move, it is frequently easier to identify them when they are moving than when they are stationary. Specifically, it is shown that certain statistical spatial and temporal features that can be derived from approximations to the motion field have invariant properties, and can be used to classify regional activities such as windblown trees, ripples on water, or chaotic fluid flow, that are characterized by complex, non-rigid motion. The technique is referred to as temporal texture analysis, in analogy to the techniques developed to classify gray-scale textures. The techniques are demonstrated on a number of real-world image sequences containing complex movement. The work has practical application in monitoring and surveillance, and as a component of a sophisticated visual system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Iterative TIN generation from digital evaluation models
Authors: Michael F. Polis, David M. McKeown Jr.
Venue: CVPR
Year: 1992

A technique for producing a triangulated irregular network (TIN) from a digital elevation model (DEM) is described. The overall goal is to produce an approximate terrain description that preserves the major topographic features using a greatly reduced set of points selected from the original DEM. The TIN generation process is iterative; at each iteration, areas in the DEM that lie outside of a user-supplied error tolerance in the TIN are identified, and points are chosen from the DEM to more accurately model these areas. Point selection involves the computation of the difference between the actual DEM and an approximate DEM. This approximate DEM is calculated by interpolating elevation points from the TIN.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Random perturbation models and performance characterization in computer vision
Authors: Visvanathan Ramesh, Robert M. Haralick
Venue: CVPR
Year: 1992

It is shown how random perturbation models can be set up for a vision algorithm sequence involving edge finding, edge linking, and gap filling. By starting with an appropriate noise model for the input data, the authors derive random perturbation models for the output data at each stage of their example sequence. These random perturbation models are useful for performing model-based theoretical comparisons of the performance of vision algorithms. Parameters of these random perturbation models are related to measures of error such as the probability of misdetection of feature units, probability of false alarm, and the probability of incorrect grouping. Since the parameters of the perturbation model at the output of an algorithm are indicators of the performance of the algorithm, one could utilize these models to automate the selection of various free parameters (thresholds) of the algorithm.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A sequential detection framework for feature tracking within computational constraints
Authors: Haydn S. Richardson, Steven D. Blostein
Venue: CVPR
Year: 1992

A unified decision-theoretic framework for automating the establishment of feature point correspondences in a temporally dense sequence of images is discussed. The approach extends a recent sequential detection algorithm to guide the detection and tracking of object feature points through an image sequence. The resulting extended feature tracks provide robust feature correspondences, for the estimation of three-dimensional structure and motion, over an extended number of image frames.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Task-specific utility in a general Bayes net vision system
Authors: Raymond D. Rimey, Christopher M. Brown
Venue: CVPR
Year: 1992

TEA is a task-oriented computer vision system that uses Bayes nets and a maximum expected-utility decision rule to choose a sequence of task-dependent and opportunistic visual operations on the basis of their cost and (present and future) benefit. The authors discuss technical problems regarding utilities, present TEA-1's utility function (which approximates a two-step lookahead), and compare it to various simpler utility functions in experiments with real and simulated scenes.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Hierarchical decomposition and axial shape description
Authors: Hillel Rom, Gérard G. Medioni
Venue: CVPR
Year: 1992

A method for producing a segmented axial description of a given shape together with a hierarchical decomposition of the shape into its parts is presented. The novelty of this approach lies in the combination of several competing approaches and tools into a unified scheme and an efficient implementation producing natural descriptions. Smooth local symmetries are used for the axial description of parts, which are suggested by curvature sign changes. Parallel symmetries are used to provide information on global relationships within the shape. This information is used for parsing shape into a hierarchy of parts. This approach uses both region and contour information, can handle shapes with corners, and addresses the issue of local versus global information, the issue of scale, and the notion of part. The method is computationally efficient, robust, and stable. Results that show that it provides an intuitive shape description are included.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Geometric primitive extraction using a genetic algorithm
Authors: Gerhard Roth, Martin D. Levine
Venue: CVPR
Year: 1992

Extracting geometric primitives from geometric sensor data is an important problem in model-based vision. A minimal subset is the smallest number of points necessary to define a unique instance of a geometric primitive. A genetic algorithm based on a minimal subset representation is used to perform primitive extraction. It is shown that the genetic approach is an improvement over random search and is capable of extracting more complex primitives than the Hough transform.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Efficient model library access by projectively invariant indexing functions
Authors: Charlie Rothwell, Andrew Zisserman, Joe L. Mundy, David A. Forsyth
Venue: CVPR
Year: 1992

Projectively invariant shape descriptors allow fast indexing into model libraries without the need for pose computation or camera calibration. Progress in building a model-based vision system for plane objects that uses algebraic projective invariants is described. A brief account of these descriptors is given, and the recognition system is described, giving examples of the invariant techniques working on real images.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Object segmentation and binding within a biologically-based neural network model of depth-from-occlusion
Authors: Paul Sajda, Leif H. Finkel
Venue: CVPR
Year: 1992

The problems of object segmentation and binding are addressed within a biologically based network model capable of determining depth from occlusion. In particular, the authors discuss two subprocesses most relevant to segmentation and binding: contour binding and figure direction. They propose that these two subprocesses have intrinsic constraints that allow several underdetermined problems in occlusion processing and object segmentation to be uniquely solved. Simulations that demonstrate the role these subprocesses play in discriminating objects and stratifying them in depth are reported. The network is tested on illusory stimuli, with the network's response indicating the existence of robust psychological properties in the system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Perceptual organization using Bayesian networks
Authors: Sudeep Sarkar, Kim L. Boyer
Venue: CVPR
Year: 1992

It is shown that the formalism of Bayesian networks provides an elegant solution, in a probabilistic framework, to the problem of integrating top-down and bottom-up visual processes as well serving as a knowledge base. The formalism is modified to handle spatial data and thus extends the applicability of Bayesian networks to visual processing. The modified form is called the perceptual inference network (PIN). The theoretical background of a PIN is presented, and its viability is demonstrated in the context of perceptual organization. The PIN imparts an active inferential and integrating nature to perceptual organization.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
On finding the ends of straight homogeneous generalized cylinders
Authors: Hiroaki Sato, Thomas O. Binford
Venue: CVPR
Year: 1992

Algorithms to detect pairs of edges that could be ends of a straight homogeneous generalized cylinder (SHGC) are proposed. Geometrical constraints for the ends of an SHGC are utilized to group edge elements and edge segments in a complex image. Two methods are investigated. The first algorithm is for a subset of SHGCs for which scaling factors of the cross section at both ends are the same. The second algorithm is for any SHGC. However, a modified version is implemented to reduce computation; given a reference and edge, it finds the edges possibly paired with it. Several examples of ends extracted from real images are reported to show the feasibility of the algorithm.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Smoothed local generalized cones: an axial representation of 3D shapes
Authors: Yoshinobu Sato, Jun Ohya, Kenichiro Ishii
Venue: CVPR
Year: 1992

The recovery of viewpoint-independent descriptions of 3D shapes from two-and-one-half dimensional images. A novel 3D shape representation called the smoothed local generalized cones (SLGCs) is proposed. This representation is suitable for recovery of the axis, because the local constraint that characterizes a data set corresponding to the same axis point, namely, the local generalized cone (LGC), is explicitly defined. The extracted axis can be used as a basis for determining a natural parameterization of the object surface. Using this parameterization, the deformable surface fitting problem results in a linear least-squares problem, so stable volumetric recovery is possible. Recovery experiments involving real 3D range images are reported.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Recovery of hierarchical part structure of 3-D shape from range image
Authors: Yoshinobu Sato, Jun Ohya, Kenichiro Ishii
Venue: CVPR
Year: 1992

A formulation of the part decomposition problem motived by the minimum-description-length (MDL) criteria is presented. Unlike previous MDL approaches which use analytic functions, a general geometric constraint, convexity, is used as a part constraint. Therefore, the method is suitable for complex natural shapes such as human faces. The recovery process consists of a bottom-up grouping process and a subsequent optimization process based on the MDL criteria. The definite causal relations of part structure between different sensitivity levels are used to recover the hierarchy of part structure. Part decomposition experiments involving real 3-D range images are reported.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Affine trackability aids obstacle detection
Authors: Harpreet S. Sawhney, Allen R. Hanson
Venue: CVPR
Year: 1992

Potential obstacles in the path of a mobile robot that can often be characterized as shallow (i.e., their extent in depth is small compared to their distance from the camera) are considered. The constraint of affine trackability is applied to automatic identification and 3-D reconstruction of shallow structures in realistic scenes. It is shown how this approach can handle independent object motion, occlusion, and motion discontinuity. Although the reconstructed structure is only a frontal plane approximation to the corresponding real structure, the robustness of depth of the approximation might be useful for obstacle avoidance, where the exact shape of an object may not be of consequence so long as collisions with it can be avoided.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Optimal nonlinear pattern restoration from noisy binary figures
Authors: Dan Schonfeld
Venue: CVPR
Year: 1992

A mathematical framework for the solution of statistical inference problems on a class of random sets is proposed. It is based on a new definition of expected pattern. The least-mean-difference estimator (restoration filter) is proved, under certain conditions, to be equivalent to the minimization of the measure of size (area) of the set-difference between the original pattern and the expected pattern of the estimated (restored) pattern. Consequently, it is proved that, under certain conditions, if the estimator (restoration filter) is unbiased, then it is the least mean difference estimator (restoration filter).< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Visual motion analysis under interceptive behavior
Authors: Rajeev Sharma, Yiannis Aloimonos
Venue: CVPR
Year: 1992

The development of the visual processes that would be needed by a mobile robot system for visually intercepting a moving target is considered. Many relevant active visual processes are proposed that provide robust input for qualitative motion control strategies. The processes for detecting independent motion and for monitoring progress toward the moving target are summarized.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Detecting parameterized curve segments using MDL and the Hough transform
Authors: Jacob Sheinvald, Byron Dom, Wayne Niblack, Saibal Banerjee
Venue: CVPR
Year: 1992

A method for detecting curve segments in a digital image is described. The method takes as input a set of edges, and produces as output the number of and parameters for the segments. The method is robust, requiring no thresholds. In place of thresholds, a model class must be provided. Using the information-theoretic minimum description length (MDL) principle, it evaluates each model in the model class, computing the optimal parameters for that model, and selects the best model as the one that gives the shortest encoding of the data and the model. Typical of such methods, the search space is extremely large. It is shown how the Hough transform (HT) may be used to reduce this search space greatly, yielding an efficient (although suboptimal) search. The result is an algorithm in which MDL overcomes standard problems with the HT, while the HT overcomes problems with MDL, and which produces a pleasing set of line segments.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>