Proceedings of the Seventh IEEE International Conference on Computer Vision

Measures of scatter are used in statistical pattern recognition to identify and select important features, computed as linear combinations of the given features. Examples include principal components and linear discriminants. The classic computational procedures require eigenvector decomposition of large matrices, and in the case of images they are only practical for identifying a low dimensional ... View full abstract»

When designing computer vision systems for the blind and visually impaired it is important to determine the orientation of the user relative to the scene. We observe that most indoor and outdoor (city) scenes are designed on a Manhattan three-dimensional grid. This Manhattan grid structure puts strong constraints on the intensity gradients in the image. We demonstrate an algorithm for detecting th... View full abstract»

The eikonal equation and variants of it are of significant interest for problems in computer vision and image processing. It is the basis for continuous versions of mathematical morphology, stereo, shape-from-shading and for recent dynamic theories of shape. Its numerical simulation can be delicate, owing to the formation of singularities in the evolving front, and is typically based or, level set... View full abstract»

A Bayesian framework for deformable pattern classification was proposed by K.W. Cheung et al. (1998), with promising results for isolated handwritten character recognition. Its performance, however degrades significantly when it is applied to detect deformable patterns in complex scenes, where the amount of outliers due to other neighboring objects or the background is usually large. Also, the fac... View full abstract»

Using a saliency measure based on the global property of contour closure, we have developed a method that reliably segments out salient contours bounding unknown objects from real edge images. The measure also incorporates the Gestalt principles of proximity and smooth continuity that previous methods have exploited. Unlike previous measures, we incorporate contour closure by finding the eigen-sol... View full abstract»

Since their debut in 1987, snakes (active contour models) have become a standard image analysis technique with several variants now in common use. We present a portable, reusable software package called “United Snakes”. The package unites the most popular snake variants, including finite difference, B-spline, and Hermite polynomial snakes within the mathematical framework of a general ... View full abstract»

Maximisation of cross correlation is a commonly used principle for intensity based object localization that gives a single estimate of location. However, to facilitate sequential inference (e.g. over time or scale) and to allow the representation of ambiguity, it is desirable to represent an entire probability distribution for object location. Although the cross correlation itself (or some functio... View full abstract»

Current vision systems are designed to perform in clear weather. Needless to say, in any outdoor application, there is no escape from “bad” weather. Ultimately, computer vision systems must include mechanisms that enable them to function (even if somewhat less reliably) in the presence of haze, fog, rain, hail and snow. We begin by studying the visual manifestations of different weathe... View full abstract»

The paper introduces a new free-form surface representation scheme for the purpose of fast and accurate registration and matching. Accurate registration of surfaces is a common task in computer vision. The proposed representation scheme captures the surface curvature information seen from certain points and produces images called surface signatures at these points. Matching signatures of different... View full abstract»

We describe two new algorithms for two-frame structure from motion from tracked point features. One is the first fast algorithm for computing an exact least-squares estimate. It exploits our observation that the rotationally invariant least-squares error can be written in a simple form that depends just on the motion. The other is essentially as accurate as the least-squares estimate and is more e... View full abstract»

An approach to extract watersheds and watercourses, as well as their corresponding valleys and hills, from images with subpixel precision is proposed. The critical points of the terrain are essential as the starting points for the construction of these separatrices. They are extracted efficiently with subpixel precision using an approach based on derivatives of Gaussian filters. The separatrices a... View full abstract»

Some issues in markerless tracking of human body motion are addressed. Extended Kalman filters have commonly been applied to kinematic variables, to combine predictions consistent with plausible motion, with the incoming stream of visual measurements. Kalman filtering is applicable only when the underlying distribution is approximately Gaussian. Often this assumption proves remarkably robust. Ther... View full abstract»

We show a learning-based method for low-level vision problems-estimating scenes from images. We generate a synthetic world of scenes and their corresponding rendered images. We model that world with a Markov network, learning the network parameters from the examples. Bayesian belief propagation allows us to efficiently find a local maximum of the posterior probability for the scene, given the imag... View full abstract»

This paper describes a Bayesian approach for modeling 3D scenes as a collection of approximately planar layers that are arbitrarily positioned and oriented in the scene. In contrast to much of the previous work on layer based motion modeling, which compute layered descriptions of 2D image motion, our work leads to a 3D description of the scene. We focus on the key problem of automatically segmenti... View full abstract»

The paper presents a novel variational method for supervised texture segmentation. The textured feature space is generated by filtering the given textured images using isotropic and anisotropic filters, and analyzing their responses as multi-component conditional probability density functions. The texture segmentation is obtained by unifying region and boundary based information as an improved Geo... View full abstract»

Existing sequential feature based registration algorithms involving search typically either select features randomly (e.g. the RANSAC approach (M. Fischler and R. Bolles, 1981)) or assume a predefined, intuitive ordering for the features (e.g. based on size or resolution). The paper presents a formal framework for computing an ordering for features which maximizes search efficiency. Features are r... View full abstract»

When a transparent surface is present between an observer and an object, an image reflected by the surface may be superimposed on the image of the observed object. We present a new approach to recover the scenes (layers) and to classify which is the reflected/transmitted one, based on imaging through a polarizing filter at two orientations. Estimates of the separate layers are obtained by weighted... View full abstract»

The light reflected from a surface depends on the scene geometry, the incident illumination and the surface material. A novel methodology is presented which extracts reflectivity information of the various materials in the scene independent of incident light and scene geometry. A scene is captured under different narrow-band color filters and the spectral derivatives of the scene are computed. The... View full abstract»

We address the problem of global registration between multiple d-dimensional point patterns with a given correspondence. The actual overlapping is not necessarily between pairs. Instead, it can be between any number of patterns. It is assumed that each pattern is a portion of an image of an unobserved object under a distinct rigid transformation. We derive an iterative solution for the problem of ... View full abstract»

Corner models in the literature have lagged behind edge models with respect to color and shading. We use both a region model, based on distributions of pixel colors, and an edge model, which removes false positives, to perform corner detection on color images whose regions contain texture. We show results on a variety of natural images at different scales that highlight the problems that occur whe... View full abstract»

Two basic problems in image interpretation are: a) determining which interpretations are the most plausible amongst many possibilities; and b) controlling the search for plausible interpretations. We address these issues using a Bayesian approach, with the plausibility ordering and search pruning based on the posterior probabilities of interpretations. However, due to the need for detailed quantit... View full abstract»

We propose a new form of energy functional for the segmentation of regions in images, and an efficient method for finding its global optima. The energy can have contributions from both the region and its boundary, thus combining the best features of region- and boundary-based approaches to segmentation. By transforming the region energy into a boundary energy, we can treat both contributions on an... View full abstract»

We consider a recent approach to recognition that uses regions to determine the pose of objects while allowing for partial occlusion of the regions. We further analyze properties of the method for planar objects undergoing projective transformations. We prove that three visible regions are sufficient to determine the transformation uniquely, and that for a large class of objects two regions are in... View full abstract»