OpenRaiser/Intern-Atlas huggingface dataset:
Wide Baseline Stereo Matching
Authors: Philip Pritchett, Andrew Zisserman
Venue: ICCV
Year: 1998

The objective of this work is to enlarge the class of camera motions for which epipolar geometry and image correspondences can be computed automatically. This facilitates matching between quite disparate views-wide baseline stereo. Two extensions are made to the current small baseline algorithms: first, and most importantly, a viewpoint invariant measure is developed for assessing the affinity of corner neighbourhoods over image pairs; second, algorithms are given for generating putative corner matches between image pairs using local homographies. Two novel infrastructure developments are also described: the automatic generation of local homographies, and the combination of possibly conflicting sets of matches prior to RANSAC estimation. The wide baseline matching algorithm is demonstrated on a number of image pairs with varying relative motion, and for different scene types. All processing is automatic.
Reading between the lines: A method for extracting dynamic 3D with Texture
Authors: Marc Proesmans, Luc Van Gool, Filip Defoort
Venue: ICCV
Year: 1998

A method is presented that extracts the 3D shape of objects, together with the surface texture. Both shape and texture are obtained from a single image. The underlying principle is based on an active technique. A high resolution, pattern is projected onto the object and the deformations as observed by a single camera yield the 3rd dimension. Furthermore, the surface texture is extracted from the same image. Because the whole procedure is based on a single image, a frame-by-frame reconstruction of a video taken with the pattern projected throughout, yields 3D shape dynamics. The paper sketches the complete system but focuses on the problem of texture extraction.
Multiscale Annealing for Real-Time Unsupervised Texture Segmentation
Authors: Jan Puzicha, Joachim M. Buhmann
Venue: ICCV
Year: 1998

We derive real-time global optimization algorithms for several clustering optimization methods used in unsupervised texture segmentation. Speed is achieved by exploiting the topological relation of features to design a multiscale optimization technique, while accuracy and global optimization properties are provided by a deterministic annealing method. Coarse grained costfunctions are derived for both central and sparse pairwise clustering, where the problem of coarsening sparse random graphs is solved by the concept of structured randomization. Annealing schedules and coarse-to-fine optimization are tightly coupled by a statistical convergence criterion derived from computational learning theory. The algorithms are benchmarked on Brodatz-like micro-texture mondrians. Results are presented for an autonomous robotics application.
Optimal Recovery of Depth from Defocused Images Using an MRF Model
Authors: A. N. Rajagopalan 0001, Subhasis Chaudhuri
Venue: ICCV
Year: 1998

A MAP-MRF based scheme is proposed for simultaneous recovery of the depth and the focused image of a scene from two defocused images. The space-variant blur parameter and the focused image of the scene are both modeled as MRFs and their MAP estimates are obtained using simulated annealing. The performance of the proposed scheme is tested on synthetic as well as real data and the estimates of the depth are found to be better than that of existing window-based techniques.
Finding Faces in Photographs
Authors: A. N. Rajagopalan 0001, K. Sunil Kumar, Jayashree Karlekar, R. Manivasakan, M. Milind Patil, Uday B. Desai, P. G. Poonacha, Subhasis Chaudhuri
Venue: ICCV
Year: 1998

Two new schemes are presented for finding human faces in a photograph. The first scheme approximates the unknown distributions of the face and the face-like manifolds wing higher order statistics (HOS). An HOS-based data clustering algorithm is also proposed. In the second scheme, the face to non-face and non-face to face transitions are learnt using a hidden Markov model (HMM). The HMM parameters are estimated corresponding to a given photograph and the faces are located by examining the optimal state sequence of the HMM. Experimental results are presented on the performance of both the schemes.
Retrieving Images by Appearance
Authors: Srinivas Ravela, R. Manmatha
Venue: ICCV
Year: 1998

A system to retrieve images using a description of the image intensity surface is presented. Gaussian derivative filters at several scales are applied to the image and low order 2D differential invariants are computed. The resulting multi-scale representation is indexed for rapid retrieval. Queries are designed by the users from an example image by selecting appropriate regions. The invariant vectors corresponding to these regions are matched with the database counterparts both in feature and coordinate space. This yields a match score per image. Images are sorted by the match score and displayed. Experiments conducted with over 1500 images of objects embedded in arbitrary backgrounds are described. It is observed that images similar in appearance and whose viewpoint is within small view variations of the query can be retrieved with an average precision of 50%.
Agent Orientated Annotation in Model Based Visual Surveillance
Authors: Paolo Remagnino, Tieniu Tan, Keith D. Baker
Venue: ICCV
Year: 1998

The paper presents an agent based surveillance system for use in monitoring scenes involving both pedestrians and vehicles. The system supplies textual descriptions for the dynamic activity occurring in the 3D world. These are derived by means of dynamic and probabilistic inference based on geometric information provided by a vision system that tracks vehicles and pedestrians. The symbolic scene annotation is given at two major levels of description: the object level and the inter-object level. At object level, each tracked pedestrian or vehicle is assigned a behaviour agent which uses a Bayesian network to infer the fundamental features of the objects' trajectory, and continuously updates its textual description. The inter-object interaction level is interpreted by a situation agent which is created dynamically when two objects are in close proximity. In the work included here the situation agent can describe a two-object interaction in terms of basic textual annotations, to summarise the dynamics of the local action.
Two-Dimensional Affine Invariants that Distribute Uniformly and can be Tuned to any Convex Feature Domain
Authors: Isidore Rigoutsos
Venue: ICCV
Year: 1998

We derive and discuss a set of parametric equations which, when given a convex 2D feature domain, K, will generate affine invariants with the property that the invariants' values are uniformly distributed in the region [0,1]/spl times/[0,1]. Definition of the shape of the convex domain K allows computation of the parameters' values and thus the proposed scheme can be tuned to a specific feature domain. The features of all recognizable objects (models) are assumed to be two-dimensional points and uniformly distributed over K. The scheme leads to improved discrimination power, improved computational-load and storage-load balancing and can also be used to determine and identify biases in the database of recognizable models (over-represented constructs of object points). Obvious enhancements produce rigid-transformation and similarity-transformation invariants with the same good distribution properties, making this approach generally applicable. An extension to the case of affine invariants for feature points in three-dimensional space, with the invariants now being uniformly distributed in the region [0,1]/spl times/[0,1]/spl times/[0,1], has also been carried out and is discussed briefly. We present results for several 2D convex domains using both synthetic data and real databases.
Automatic Registration of 3-D Ultrasound Images
Authors: Robert Rohling, Andrew H. Gee, Laurence H. Berman
Venue: ICCV
Year: 1998

One of the most promising applications of 3-D ultrasound lies in the visualisation and volume estimation of internal 3-D structures. Unfortunately, artifacts and speckle make automatic analysis of the data difficult. In this paper we investigate the use of 3-D spatial compounding to improve data quality, and find that accurate registration is the key. A correlation-based registration technique is applied to 3-D ultrasound data acquired from in-vivo examinations of a human gall bladder. We find that the registration technique performs well, and visualisation and segmentation of the compounded data are clearly improved.
A Metric for Distributions with Applications to Image Databases
Authors: Yossi Rubner, Carlo Tomasi, Leonidas J. Guibas
Venue: ICCV
Year: 1998

We introduce a new distance between two distributions that we call the Earth Mover's Distance (EMD), which reflects the minimal amount of work that must be performed to transform one distribution into the other by moving "distribution mass" around. This is a special case of the transportation problem from linear optimization, for which efficient algorithms are available. The EMD also allows for partial matching. When used to compare distributions that have the same overall mass, the EMD is a true metric, and has easy-to-compute lower bounds. In this paper we focus on applications to image databases, especially color and texture. We use the EMD to exhibit the structure of color-distribution and texture spaces by means of Multi-Dimensional Scaling displays. We also propose a novel approach to the problem of navigating through a collection of color images, which leads to a new paradigm for image database search.
Visual Routines for Autonomous Driving
Authors: Garbis Salgian, Dana H. Ballard
Venue: ICCV
Year: 1998

The paper describes visual routines based on models of color and shape, as well as crucial issues involving the scheduling of such routines. The visual routines are developed in a unique platform. The view from a car driving in a simulated world is feed into a Datacube pipeline video processor. The use of this simulation provides a flexible environment from which to set crucial image processing parameters of the individual routines. In addition to the simulations, the routines are also tested in similar images generated by driving in the real world, to assure the generalizability of the simulation.
Recognizing Novel 3-D Objects Under New Illumination and Viewing Position Using a Small Number of Examples
Authors: Erez Sali, Shimon Ullman
Venue: ICCV
Year: 1998

A method is presented for class-based recognition using a small number of example views taken under several different viewing conditions. The main emphasis is on using a small number of examples. Previous work assumed that the set of examples is sufficient to span the entire space of possible objects, and that in generalizing to a new viewing conditions a sufficient number of previous examples under the new conditions will be available to the recognition system. Here we have considerably relaxed these assumptions and consequently obtained good class-based generalization from a small number of examples, even a single example view, for both viewing position and illumination changes. In addition, previous class-based approaches only focused on viewing position changes and did not deal with illumination changes. Here we used a class-based approach that can generalize for both illumination and viewing position changes. The method was applied to face and car model images. New views under viewing position and illumination changes were synthesized from a small number of examples.
Bilinear Voting
Authors: Guillermo Sapiro
Venue: ICCV
Year: 1998

A geometric-vision approach to solve bilinear problems in general, and the color constancy and illuminant estimation problem in particular, is presented in this paper. We show a general framework, based on ideas from the generalized (probabilistic) Hough transform, to estimate the unknown variables in the bilinear form. In the case of illuminant and reflectance estimation in natural images, each image pixel "votes" for possible illuminants (or reflectance), and the estimation is based on cumulative votes. In the general case, the voting is for the parameters of the bilinear model. The framework is natural for the introduction of physical constraints. For the case of illuminant estimation, we briefly show the relation of this work with previous algorithms for color constancy, and present examples.
Fish-Scales: Representing Fuzzy Manifolds
Authors: Radim Sára, Ruzena Bajcsy
Venue: ICCV
Year: 1998

We address the problem of automatically reconstructing m-manifolds of unknown topology from unorganized points in metric p-spaces obtained from a noisy measurement process . The point set is first approximated by a collection of oriented primitive fuzzy sets over a range of resolutions. Hierarchical multiresolution representation is then computed based on the relation of relative containment defined on the collection. Finally, manifold structure is recovered by establishing connectivity between these primitives based on proximity, compatibility of position and orientation and local topological constraints. The method has been successfully applied to the problem of surface reconstruction from polynocular-stereo data with many outliers.
Separation of Transparent Layers Using Focus
Authors: Yoav Y. Schechner, Nahum Kiryati, Ronen Basri
Venue: ICCV
Year: 1998

Consider situations where the depth at each point in the scene is multi-valued due to the presence of a virtual image semi-reflected by a transparent surface. The semi-reflected image is linearly superimposed on the image of the object that is behind the transparent surface. A novel approach is proposed for the recovery of the superimposed layers. By searching for the images in which either of the objects (layers) is focused, the transparent areas are detected and an estimate of the depth map of each layer is obtained. As a result of the focusing, an initial separation of the layers is achieved. The separation is enhanced via mutual blurring of the perturbing components in the images, based on the depths estimate and the parameters of the imaging system.
Transinformation for Active Object Recognition
Authors: Bernt Schiele, James L. Crowley
Venue: ICCV
Year: 1998

This article develops an analogy between object recognition and the transmission of information through a channel based on the statistical representation of the appearances of 3D objects. This analogy provides a means to quantitatively evaluate the contribution of individual receptive field vectors, and to predict the performance of the object recognition process. Transinformation also provides a quantitative measure of the discrimination provided by each viewpoint, thus permitting the determination of the most discriminant viewpoints. As an application, the article develops an active object recognition algorithm which is able to resolve ambiguities inherent in a single-view recognition algorithm.
Computing Ritz Approximations of Primary Images
Authors: Haim Schweitzer
Venue: ICCV
Year: 1998

Ritz vectors approximate eigenvectors that are a common choice for primary images in content based indexing. They can be computed efficiently even when the images are accessed through slow communication such as the Internet. We develop an algorithm that computes Ritz vectors in one pass through the images. When iterated, the algorithm can recover the exact eigenvectors. In applications to image indexing and learning it may be necessary to compute primary images for indexing many sub-categories of the image set. The proposed algorithm can compute these age data. Similar computation by other algorithms is much more costly even when access to the images is inexpensive.
Indexing Images by Trees of Visual Content
Authors: Haim Schweitzer
Venue: ICCV
Year: 1998

An unsupervised algorithm for arranging an image database as a binary tree is described. Tree nodes are associated with image subsets, maintaining the property that the similarity among the images associated with the children of a node is higher than the similarity among the images associated with the parent node. Experiments with datasets of hundreds and thousands of images show that shallow trees can produce clustering into "meaningful" classes. Visual-content search trees can be used to automate image retrieval by content, or help a human to interactively search for images.
Active Blobs
Authors: Stan Sclaroff, John Isidoro
Venue: ICCV
Year: 1998

A new region-based approach to nonrigid motion tracking is described. Shape is defined in terms of a deformable triangular mesh that captures object shape plus a color texture map that captures object appearance. Photometric variations are also modeled. Nonrigid shape registration and motion tracking are achieved by posing the problem as an energy-based, robust minimization procedure. The approach provides robustness to occlusions, wrinkles, shadows, and specular highlights. The formulation is tailored to rake advantage of texture mapping hardware available in many workstations, PCs, and game consoles. This enables nonrigid tracking at speeds approaching video rate.
Plenoptic Image Editing
Authors: Steven M. Seitz, Kiriakos N. Kutulakos
Venue: ICCV
Year: 1998

This paper presents a new class of interactive image editing operations designed to maintain consistency between multiple images of a physical 3D scene. The distinguishing feature of these operations is that edits to any one image propagate automatically to all other images as if the (unknown) 3D scene had itself been modified. The modified scene can then be viewed interactively from any other camera viewpoint and under different scene illuminations. The approach is useful first as a power-assist that enables a user to quickly modify many images by editing just a few, and second as a means for constructing and editing image-based scene representations by manipulating a set of photographs. The approach works by extending operations like image painting, scissoring, and morphing so that they alter a scene's generalized plenoptic function in a physically-consistent way, thereby affecting scene appearance from all viewpoints simultaneously. A key element in realizing these operations is a new volumetric decomposition technique for reconstructing an scene's plenoptic function from an incomplete set of camera viewpoints.
Construction and Refinement of Panoramic Mosaics with Global and Local Alignment
Authors: Heung-Yeung Shum, Richard Szeliski
Venue: ICCV
Year: 1998

This paper presents techniques for constructing full view panoramic mosaics form sequences of images. Our representation associates a rotation matrix (and optionally a focal length) with each input image, rather than explicitly projecting all of the images onto a common surface (e.g., a cylinder). In order to reduce accumulated registration errors we apply global alignment (block adjustment) to whole sequence of images, which results in an optimal image mosaic (in the least squares sense). To compensate for small amounts of motion parallax introduced by translations of the camera and other unmodeled distortions we develop a local alignment (deghosting) technique which warps each image based on the results of pairwise local image registrations. By combining both global and local alignment we significantly improve the quality of our image mosaics thereby enabling the creation of full view panoramic mosaics with hand-held cameras.
Hyperbolic "Smoothing" of Shapes
Authors: Kaleem Siddiqi, Allen R. Tannenbaum, Steven W. Zucker
Venue: ICCV
Year: 1998

We have been developing a theory of generic 2-D shape based on a reaction-diffusion model from mathematical physics. The description of a shape is derived from the singularities of a curve evolution process driven by the reaction (hyperbolic) term. The diffusion (parabolic) term is related to smoothing and shape simplification. However, the unification of the two is problematic, because the slightest amount of diffusion dominates and prevents the formation of generic first-order shocks. The technical issue is whether it is possible to smooth a shape, in any sense, without destroying the shocks. We now report a constructive solution to this problem, by embedding the smoothing term in a global metric against which a purely hyperbolic evolution is performed from the initial curve. This is a new flow for shape, that extends the advantages of the original one. Specific metrics are developed, which lead to a natural hierarchy of shape features, analogous to the simplification one might perceive when viewing an object from increasing distances. We illustrate our new flow with a variety of examples.
Egomotion Estimation Using Log-Polar Images
Authors: César Silva, José Santos-Victor
Venue: ICCV
Year: 1998

We address the problem of egomotion estimation of a monocular observer moving with arbitrary translation and rotation in an unknown environment, using log-polar images. The method we propose is uniquely based on the spatio-temporal image derivatives, or the normal flow. Thus, we avoid computing the complete optical flow field, which is an ill-posed problem due to the aperture problem. We use a search paradigm based on geometric properties of the normal flow field, and consider a family of search subspaces to estimate the egomotion parameters. These algorithms are particularly well-suited for the log-polar image geometry, as we use a selection of special normal flow, vectors with simple representation in log-polar coordinates. This approach highlights the close coupling between algorithmic aspects and the sensor geometry (retina physiology), often, found in nature. Finally, we present and discuss a set of experiments, for various kinds of camera motions, which show encouraging results.
Automatic Model Construction, Pose Estimation, and Object Recognition from Photographs using Triangular Splines
Authors: Steve Sullivan, Jean Ponce
Venue: ICCV
Year: 1998

This paper proposes a method for automatically constructing triangular G/sup 1/ spline models of complex three-dimensional objects from a few registered photographs. These models are used for pose estimation from monocular silhouette data and they form the basis for a simple recognition strategy. The proposed approach is demonstrated by several experiments.
Recognition of 3D Free-form Objects Using Segment-based Stereo Vision
Authors: Yasushi Sumi, Yoshihiro Kawai, Takashi Yoshimi, Fumiaki Tomita
Venue: ICCV
Year: 1998

We propose a new method to recognize 3D free-form objects from their apparent contours. It is the extension of our established method to recognize objects with fixed edges. Object models are compared with 3D boundaries which are extracted by segment-based stereo vision. Based on the local shapes of the boundaries, candidate transformations are generated. The candidates are verified and adjusted based on the whole shapes of the boundaries. The models are built from all-around range data of the objects. Experimental results show the effectiveness of the method.