OpenRaiser/Intern-Atlas huggingface dataset:
Segmentation and 2D motion estimation by region fragments
Authors: Minoru Etoh, Yoshiaki Shirai
Venue: ICCV
Year: 1993

A central problem in estimating multiple image motions is that 2-D motion estimation and region segmentation are mutually dependent. The authors present a new region description method for dealing with this mutual dependence problem. Segmentation and motion estimation are simultaneously performed by a clustering process based on color, motion, and pixel position. As a result of the clustering, an image is decomposed into region fragments. Each fragment is characterized by distribution parameters of color, pixel positions, and spatiotemporal intensity gradients. The image is described by the parameters of the region fragments; 2-D motion vectors for each fragment are obtained from the distribution parameters of the intensity gradients. By combining those features in the clustering process, regions are segmented more precisely, motion boundaries are not blurred, and the 2-D motions are obtained even in noisy areas. Experimental results are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Head-centered orientation strategies in animate vision
Authors: Enrico Grosso, Dana H. Ballard
Venue: ICCV
Year: 1993

The authors consider orienting, that is, establishing and maintaining a spatial relation between a motorized pair of cameras (the eye-head system) and a static or a moving object tracked over time. Motivated by physiological evidence, they propose a simple set of vision-based strategies aimed to perform head, eye, and body movements in a complex environment. Fixation is shown to be an essential feature in visual servoing, and is used to decouple control on head rotational degrees of freedom, making possible a metric-less approach to the orientation problem. An implementation of these strategies, using a binocular camera system mounted on a PUMA 700 robotic system, demontrated the effectiveness of the approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Using hyperquadrics for shape recovery from range data
Authors: Song Han, Dmitry B. Goldgof, Kevin W. Bowyer
Venue: ICCV
Year: 1993

Superquadric is an implicit model which was recently introduced and successfully applied in computer vision research. The authors introduce its generalization, the use of the hyperquadric models, for computer vision applications, and focus on its utilization for shape recovery from range data. The hyperquadric model can be composed of any number of terms. Its geometric bound is an arbitrary convex polyhedron, and thus it can describe more complex shapes than the superquadric. A fitting method is proposed that starts with a rough fit with only two terms in the 2-D case or three terms in the 3-D case, and then adds additional terms to improve the fit. The experiments indicate that the use of hyperquadrics is a promising paradigm for shape representation and recovery in computer vision.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Distance accumulation and planar curvature
Authors: Joon Hee Han, Timothy Poston
Venue: ICCV
Year: 1993

The authors present a method, called distance accumulation, of computing features of closed planar boundaries of 2-D digital images, or closed curves. Distance accumulation is computed by accumulating the distance from a point in the boundary to a chord specified by moving end points. Experimental results with simulated and real images showed its robustness. The analysis of its relation to planar curvature matches experimental results well. >
Combining stereo and motion analysis for direct estimation of scene structure
Authors: Keith J. Hanna, Neil E. Okamoto
Venue: ICCV
Year: 1993

The authors describe an algorithm based on hierarchical model-based estimation and refinement that aims to make best use of the information in stereo and motion data sets to estimate scene structure. Information from both data sets is used to compute simultaneously stereo and motion correspondences that are consistent with a single scene structure. One result is that local ambiguities in information provided by one data set are resolved by information provided by the other data set. The algorithm uses an infinitesimal rigid-body motion model to estimate relative camera orientation and local ranges for both the stereo and motion components of the data. If the relative orientation of the cameras in the stereo data set is known, the solution proposed can be re-derived using fixed rather than variable camera parameters for the stereo data set.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A computational model of neural contour processing: Figure-ground segregation and illusory contours
Authors: Friedrich Heitger, Rüdiger von der Heydt
Venue: ICCV
Year: 1993

The detection of occluding contours in images of 3-D scenes is a fundamental problem of vision. The authors present a computational model of contour processing that was suggested by neurophysiological recordings from the monkey visual cortex. The model uses convolutions and nonlinear operations, but no feedback loops. Contours are defined by the local maxima of the responses of a contour operator that sums a representation of contrast borders and a grouping signal. The grouping consists of convolving a representation of key-points, such as T-junctions, corners, and line ends, with a set of orientation selective kernels, and a nonlinear pairing operation. The grouping scheme is selective based on whether the configuration of key-points is consistent with the interpretation of occlusion. The resulting contour representation includes an indicator of figure-ground direction. It is shown that the model reproduces illusory contours in accurate agreement with perception and generates representations of occluding contours on images of natural scenes that are more complete and less cluttered by spurious connections of foreground and background than those obtained by conventional edge detection operators.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Interpretation of natural scenes using multi-parameter default models and qualitative constraints
Authors: Michael Hild, Yoshiaki Shirai
Venue: ICCV
Year: 1993

High variability of object features and bad local feature separation of object classes are the main causes for the difficulties encountered during the interpretation of ground-level natural scenes. The authors propose a knowledge-based scene classification and segmentation method. The first stage carries out object classification on the basis of known local feature default models. It then searches for regions which satisfy qualitative constraints in the classified object images and selects good, approximate object region candidates, using multiple features. This approach is constrained in a top-down manner by the local feature default model and qualitative constraints while at the same time operating in a data-driven style through automatic threshold value and window size selection mechanisms. The second stage extends and refines the result of the first stage by performing a constrained search for object boundaries.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Estimation of the light source distribution and its use in integrated shape recovery from stereo and shading
Authors: Darrell R. Hougen, Narendra Ahuja
Venue: ICCV
Year: 1993

The authors deal with estimation of the light source distribution and its use in surface shape estimation by the methods of stereo and shading. There are many advantages to integrating stereo and shading information. However, shape from shading algorithms are limited in their applicability by the assumption of overly simplistic models of the light source distribution. A more complete representation is described in which the lighting model makes use of multiple fixed point sources located at infinity. Methods of estimating the model parameters are developed, and a method of estimating the surface shape given the albedo and source distribution is presented. The shading algorithm is combined with a stereo algorithm in an integrated approach that is designed to handle albedo variations through the use of color images.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Tracking non-rigid objects in complex scenes
Authors: Daniel P. Huttenlocher, Jae J. Noh, William Rucklidge
Venue: ICCV
Year: 1993

The authors describe a model-based method for tracking nonrigid objects moving in a complex scene. The method operates by extracting two-dimensional models of an object from a sequence of images. The basic idea underlying the technique is to decompose the image of a solid object moving in space into two components: a two-dimensional motion and a two-dimensional shape change. The motion component is factored out and the shape change is represented explicitly by a sequence of two-dimensional models, one corresponding to each image frame. The major assumption underlying the method is that the two-dimensional shape of an object will change slowly from one frame to the next. There is no assumption, however, that the two-dimensional image motion between successive frames will be small.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Renormalization for unbiased estimation
Authors: Kenichi Kanatani
Venue: ICCV
Year: 1993

In many computer vision problems, it is necessary to robustly estimate parameter values from a large quantity of image data. In such problems, least-squares minimization is computationally the most convenient and practical solution method. The author shows that the least-squares solution is in general statistically biased in the presence of noise. A scheme called renormalization that iteratively removes the statistical bias by automatically adjusting to the image noise is presented. It is applied to the problem of estimating vanishing points and focuses of expansion and conic fitting.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A quantitative methodology for analyzing the performance of detection algorithms
Authors: Tapas Kanungo, Mysore Y. Jaisimha, John Palmer, Robert M. Haralick
Venue: ICCV
Year: 1993

The authors present a methodology for designing experiments to characterize detection algorithms. The usual method is to vary parameters of the input images or parameters of the algorithms and then construct operating curves that relate the probability of misdetection and false alarm for each parameter setting. Such an analysis does not integrate the performance of the numerous operating curves. A methodology is outlined for summarizing many operating curves into a few performance curves. This methodology is adapted from the human psychophysics literature and is general to any detection algorithm. The central concept is to measure the effect of variables in terms of the equivalent effect of a critical signal variable. The methodology is demonstrated by comparing the performance of two line detection algorithms.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Multiscale Markov random field models for parallel image classification
Authors: Zoltan Kato, Marc Berthod, Josiane Zerubia
Venue: ICCV
Year: 1993

The authors consider multiscale Markov random field (MRF) models. It is well known that multigrid methods can improve significantly the convergence rate and the quality of the final results of iterative relaxation techniques. A hierarchical model is proposed, which consists of a label pyramid and a whole observation field. The parameters of the coarse grid can be derived by simple computation from the finest grid. In the label pyramid, a new local interaction is introduced between two neighbor grids. This model gives a relaxation algorithm which can be run in parallel on the entire pyramid. The model allows propagation of local interactions more efficiently, giving estimates closer to the global optimum for deterministic as well as for stochastic relaxation schemes. It can also be seen as a way to incorporate cliques with far apart sites for a reasonable price.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Probabilistic relaxation for matching problems in computer vision
Authors: Josef Kittler, William J. Christmas, Maria Petrou
Venue: ICCV
Year: 1993

The authors present the theory of probabilistic relaxation for matching symbolic structures, derive as limiting cases the various heuristic formulas used by researchers in matching problems, and state the conditions under which they apply. They successfully apply the theory to the problem of matching and recognizing aerial road network images based on road network models and to the problem of edge matching in a stereo pair. For this purpose, each line network is represented by an attributed relational graph where each node is a straight line segment characterized by certain attributes and related with every other node via a set of binary relations.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A note on existence and uniqueness in shape from shading
Authors: Ryszard Kozera
Venue: ICCV
Year: 1993

Shape recovery of a smooth Lambertian surface illuminated by one, two, or three distant light sources is discussed. In the case of three light-sources, it is shown that the corresponding system of three first-order nonlinear partial differential equations has a unique solution. In the case of one overhead light-source, the existence and uniqueness of solutions to the corresponding eikonal equation are discussed. With regard to existence, two classes of shading patterns are shown for which no genuine shapes exist. In connection with uniqueness, circularly symmetric eikonal equations are revealed for which there exist circularly symmetric and non-circularly symmetric smooth solutions of special form.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A perceptually plausible model for global symmetry detection
Authors: Francois Labonte, Yerucham Shapira, Paul Cohen 0001
Venue: ICCV
Year: 1993

The authors consider the problem of detecting global symmetry in images consisting of dense arrangements of local features, such as dots or oriented segments. Images of this kind are encountered in textured scenes or field-type pictorial representations. The proposed computational model, elaborated on the basis of several psychophysical experiments, assumes a precedence of grouping over symmetry detection and consists of three stages: a grouping stage, in which clusters are formed among local elements presenting a sufficient level of mutual affinity; a symmetry detection stage, in which pairs of symmetrical clusters are discovered and their axes of symmetry determined; and a symmetry subsumption stage, in which an attempt is made to detect more global symmetries. An implementation of the model is described. Results are presented showing a good agreement of the model's performance with human symmetry perception.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Motion detection robust to perturbations: A statistical regularization and temporal integration framework
Authors: Jean-Michel Létang, Veronique Rebuffel, Patrick Bouthemy
Venue: ICCV
Year: 1993

The authors present a scheme for motion detection exploiting temporal integration and local contextual information. A multiscale temporal decomposition is supplied to the original sequence. Change detection is performed using a likelihood test at each temporal scale. The decision process is formalized within a statistical regularization framework and takes advantage of a tracking module. Motion detection is achieved by minimizing an energy function. This function involves three terms, expressing (1) adequacy between temporal variations at different scales and motion labels, (2) local spatial regularization, and (3) coherence between temporal prediction of change area locations and motion labels. Experimental results on real scenes are reported.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A finite element model for 3D shape reconstruction and nonrigid motion tracking
Authors: Tim McInerney, Demetri Terzopoulos
Venue: ICCV
Year: 1993

The authors present a physics-based approach for recovering the 3-D shape and tracking the motion of nonrigid objects using a 3-D elastically deformable balloon model. The balloon model is based on a thin-plate under tension spline which deforms to fit visual data according to internal forces stemming from the elastic properties of the surface and external forces which are produced from the data. The finite element method is used to represent the model as a continuous surface. A natural finite element is used whose nodal variables comprise the position of the surface plus its first and second partial derivatives, reflecting each of the partial derivatives that occur in the spline's strain energy functional. Hence, the model directly estimates all the information needed to measure the differential geometric properties of the fitted surface. The balloon model was applied to the reconstruction of 3-D objects with irregular shape features. Its effectiveness is demonstrated in extracting the left ventricular surface and tracking its nonrigid motion in dynamic computerized tomography volume images.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
3D object recognition by indexing structural invariants from multiple views
Authors: Rakesh Mohan, Daphna Weinshall, Ramesh R. Sarukkai
Venue: ICCV
Year: 1993

The authors present a method for 3-D object recognition from 2-D image sequences. The system uses feature points tracked over three or more views to compute structural invariants, which serve as 3-D shape representations. Object recognition is performed by using these Euclidean invariants as indices into a high-dimensional shape table. The use of indexing eliminates any need for matching models to images. In addition, the representation of 3-D objects is extracted from 2-D views, eliminating the cumbersome burden of having to obtain 3-D models. The proposed scheme was implemented using a mixed database of real and simulated objects. Experiments are outlined that show good recognition results on real objects and simulated objects corrupted with noise.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Silhouette-based object recognition through curvature scale space
Authors: Farzin Mokhtarian, Hiroshi Murase
Venue: ICCV
Year: 1993

A complete and practical isolated-object recognition system has been developed which is very robust with respect to scale, position and orientation changes of the objects as well as noise and local deformations of shape due to perspective projection, segmentation errors and non-rigid material used in some objects. The system has been tested on a wide variety of 3-D objects with different shapes and surface properties. A light-box setup is used to obtain silhouette images which are segmented to obtain the physical boundaries of the objects which are classified as either convex or concave. Convex curves are recognized using their four high-scale curvature extrema points. Curvature scale space (CSS) representations are computed for concave curves. The CSS representation is a multi-scale organization of the natural invariant features of a curve. A three-stage coarse-to-fine matching algorithm quickly detects the correct object in each case.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Reactions to peripheral image motion using a head/eye platform
Authors: David William Murray 0001, Philip F. McLauchlan, Ian D. Reid 0001, Paul M. Sharkey
Venue: ICCV
Year: 1993

The authors demonstrate four real-time reactive responses to movement in everyday scenes using an active head/eye platform. They first describe the design and realization of a high-bandwidth four-degree-of-freedom head/eye platform and visual feedback loop for the exploration of motion processing within active vision. The vision system divides processing into two scales and two broad functions. At a coarse, quasi-peripheral scale, detection and segmentation of new motion occurs across the whole image, and at fine scale, tracking of already detected motion takes place within a foveal region. Several simple coarse scale motion sensors which run concurrently at 25 Hz with latencies around 100 ms are detailed. The use of these sensors are discussed to drive the following real-time responses: (1) head/eye saccades to moving regions of interest; (2) a panic response to looming motion; (3) an opto-kinetic response to continuous motion across the image and (4) smooth pursuit of a moving target using motion alone.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
The critical sets of lines for camera displacement estimation: A mixed Euclidean-projective and constructive approach
Authors: Nassir Navab, Olivier D. Faugeras, Thierry Viéville
Venue: ICCV
Year: 1993

The authors consider the problem of recovering the relative displacements of a camera by using line matches in three views. In particular, they try to find whether there exist sets of 3-D lines such that irrespective of how many lines are observed there will always be several solutions to the relative displacement estimation problem. Recently, T. Buchanan (1992) provided a first analysis of the problem in which he gave a positive answer. Here, an attempt is made to build on his work and extend it in several directions. First, his purely projective analysis is cast in a more Euclidean framework better suited to applications. Second, his critical set is related to those of previously published algorithms. Third, the algebraic equations are introduced and an effective, i.e., computational, approach is provided for describing these critical sets in terms of simple geometric properties. This has allowed analysis of the structure of the critical sets.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Reflectance ratio: A photometric invariant for object recognition
Authors: Shree K. Nayar, Ruud M. Bolle
Venue: ICCV
Year: 1993

Neighboring points on a smoothly curved surface have similar surface orientations and illumination conditions. Hence, their brightness values can be used to compute the ratio of their reflectance coefficients. Based on this observation, an efficient algorithm is developed that estimates a reflectance ratio for each region in an image with respect to its background. The region reflectance ratio represents a physical property of a region that is invariant to the illumination conditions. The ratio invariant is used to recognize objects from a single brightness image of a scene. Experimental results demonstrate the power of using reflectance and geometric properties of objects simultaneously.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>