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A novel active-contour method is presented and applied to pose refinement and tracking. The main innovation is that no "features" are detected at any stage: contours are simply assumed to remove statistical dependencies between pixels on opposite sides ...

We present a system that is capable of segmenting, detecting and tracking multiple people in a cluttered scene using multiple synchronized cameras located far from each other. The system improves upon existing systems in many ways including: (1)We do ...

In this paper, we study a family of analytical probability models for images within the spectral representation framework. First the input image is decomposed using a bank of filters, and probability models are imposed on the filter outputs (or spectral ...

This paper presents a theory for constructing and computing velocity-adapted scale-space filters for spatio-temporal image data. Starting from basic criteria in terms of time-causality, time-recursivity, locality and adaptivity with respect to motion ...

The problem of establishing image-to-image correspondences is fundamental in computer vision. Recently, several wide baseline matching algorithms capable of handling large changes of viewpoint have appeared. By computing feature values from image data, ...

We present techniques for improving the speed of robust motion estimation based on random sampling of image features. Starting from Torr and Zisserman's MLESAC algorithm, we address some of the problems posed from both practical and theoretical ...

We derive the decomposition of the anisotropic Gaussian in a one dimensional Gauss filter in the x -direction followed by a one dimensional filter in a non-orthogonal direction . So also the anisotropic Gaussian can be decomposed by dimension. This ...

The propose of this paper is to introduce a new regularization formulation for inverse problems in computer vision and image processing that allows one to reconstruct second order piece-wise smooth images, that is, images consisting of an assembly of ...

This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such transformations introduce significant changes in the point location as ...

In order to investigate the deep structure of Gaussian scale space images, one needs to understand the behaviour of critical points under the influence of parameter-driven blurring. During this evolution two different types of special points are ...

A large part of "image processing" involves the computation of significant points, curves and areas ("features"). These can be defined as loci where absolute differential invariants of the image assume fiducial values, taking spatial scale and intensity ...

In many vision problems, the observed data lies in a nonlinear manifold in a high-dimensional space. This paper presents a generic modelling scheme to characterize the nonlinear structure of the manifold and to learn its multimodal distribution. Our ...

In order to investigate the deep structure of Gaussian scale space images, one needs to understand the behaviour of spatial critical points under the influence of blurring. We show how the mathematical framework of catastrophe theory can be used to ...

This paper proposes an image matching method that is robust to illumination variation and affine distortion. Our idea is to do image matching through establishing an imaging function that describes the functional relationship relating intensity values ...

The performances of many image analysis tasks depend on the image resolution at which they are applied. Traditionally, resolution selection methods rely on spatial derivatives of image intensities. Differential measurements, however, are sensitive to ...

Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently employed in computer vision. The first technique draws from the projection pursuit ...

Nonlinear partial differential equations (PDE) are now widely used to regularize images. They allow to eliminate noise and artifacts while preserving large global features, such as object contours. In this context, we propose a geometric framework to ...

The modal correspondence method of Shapiro and Brady aims to match point-sets by comparing the eigenvectors of a pairwise point proximity matrix. Although elegant by means of its matrix representation, the method is notoriously susceptible to ...

We introduce a new type of local feature based on the phase and amplitude responses of complex-valued steerable filters. The design of this local feature is motivated by a desire to obtain feature vectors which are semi-invariant under common image ...

Independent representations have recently attracted significant attention from the biological vision and cognitive science communities. It has been 1) argued that properties such as sparseness and independence play a major role in visual perception, and ...

We derive a probabilistic multi-scale model for contour completion based on image statistics. The boundaries of human segmented images are used as "ground truth". A probabilistic formulation of contours demands a prior model and a measurement model. ...

We investigate the statistics of local geometric structures in natural images. Previous studies [13,14] of high-contrast 3 3 natural image patches have shown that, in the state space of these patches, we have a concentration of data points along a low-...

The Beltrami flow [13,14] is one of the most effective denoising algorithms in image processing. For gray-level images, we show that the Beltrami flow equation can be arranged in a reaction-diffusion form. This reveals the edge-enhancing properties of ...

A new feature detection technique is presented that utilises local radial symmetry to identify regions of interest within a scene. This transform is significantly faster than existing techniques using radial symmetry and offers the possibility of real-...

Quadrature filters are a well known method of low-level computer vision for estimating certain properties of the signal, as there are local amplitude and local phase. However, 2D quadrature filters suffer from being not rotation invariant. Furthermore, ...

Edge detection depends not only upon the assumed model of what an edge is, but also on how this model is represented. The problem of how to represent the edge model is typically neglected, despite the fact that the representation is a bottleneck for ...

We address the issue of regularizing Osher and Rudin's shock filter, used for image deblurring, in order to allow processes that are more robust against noise. Previous solutions to the problem suggested adding some sort of diffusion term to the shock ...

There has been considerable success in automated reconstruction for image sequences where small baseline algorithms can be used to establish matches across a number of images. In contrast in the case of widely separated views, methods have generally ...

Estimating the parameters of a pencil of lines is addressed. A statistical model for the measurements is developed, from which the Cramer Rao lower bound is determined. An estimator is derived, and its performance is simulated and compared to the bound. ...

Natural images are the composite consequence of multiple factors related to scene structure, illumination, and imaging. Multilinear algebra, the algebra of higher-order tensors, offers a potent mathematical framework for analyzing the multifactor ...