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In this paper we revisit local feature detectors/descriptors developed for 2D images and extend them to the more general framework of scalar fields defined on 2D manifolds. We provide methods and tools to detect and describe features on surfaces equiped with scalar functions, such as photometric information. This is motivated by the growing need for(More)
In this paper, we address the problem of surface tracking in multiple camera environments and over time sequences. In order to fully track a surface undergoing significant deformations, we cast the problem as a mesh evolution over time. Such an evolution is driven by 3D displacement fields estimated between meshes recovered independently at different time(More)
This paper addresses the problem of describing surfaces using local features and descriptors. While methods for the detection of interest points in images and their description based on local image features are very well understood, their extension to discrete manifolds has not been well investigated. We provide a methodological framework for analyzing(More)
Most of the algorithms dealing with image based 3-D reconstruction involve the evolution of a surface based on a minimization criterion. The mesh parametrization, while allowing for an accurate surface representation, suffers from the inherent problems of not being able to reliably deal with self-intersections and topology changes. As a consequence, an(More)
This paper proposes a novel approach to anomalous behaviour detection in video. The approach is comprised of three key components. First, distributions of spatiotemporal oriented energy are used to model behaviour. This representation can capture a wide range of naturally occurring visual spacetime patterns and has not previously been applied to anomaly(More)
Triangulated meshes have become ubiquitous discrete surface representations. In this paper, we address the problem of how to maintain the manifold properties of a surface while it undergoes strong deformations that may cause topological changes. We introduce a new self-intersection removal algorithm, TransforMesh, and propose a mesh evolution framework(More)
In this paper we address the problem of recovering structure and motion from a large number of intrinsically calibrated perspective cameras. We describe a method that combines (1) weak-perspective reconstruction in the presence of noisy and missing data and (2) an algorithm that updates weak-perspective reconstruction to perspective reconstruction by(More)
This paper proposes a neuronal-based solution to active visual search, that is, visual search for a given target in displays that are too large in spatial extent to be inspected covertly. Recent experimental data from behaving, fixating monkeys is used as a guide and this is the first model to incorporate such data. The strategy presented here includes(More)
In this paper we address the problem of building a class of robust factorization algorithms that solve for the shape and motion parameters with both affine (weak perspective) and perspective camera models. We introduce a Gaussian/uniform mixture model and its associated EM algorithm. This allows us to address parameter estimation within a data clustering(More)
A number of computational models of visual attention exist, but making comparisons is difficult due to the incompatible implementations and levels at which the simulations are conducted. To address this issue, we have developed a general-purpose neural network simulator that allows all of these models to be implemented in a unified framework. The simulator(More)