Spyridon Leonardos

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This paper addresses the challenge of 3D full-body human pose estimation from a monocular image sequence. Here, two cases are considered: (i) the image locations of the human joints are provided and (ii) the image locations of joints are unknown. In the former case, a novel approach is introduced that integrates a sparsity-driven 3D geometric prior and(More)
We investigate the problem of estimating the 3D shape of an object, given a set of 2D landmarks in a single image. To alleviate the reconstruction ambiguity, a widely-used approach is to confine the unknown 3D shape within a shape space built upon existing shapes. While this approach has proven to be successful in various applications, a challenging issue(More)
We investigate the problem of estimating the 3D shape of an object defined by a set of 3D landmarks, given their 2D correspondences in a single image. A successful approach to alleviating the reconstruction ambiguity is the 3D deformable shape model and a sparse representation is often used to capture complex shape variability. But the model inference is(More)
We propose a second order stochastic dynamical model for generic articulated objects whose state space is a Riemannian manifold naturally suggested by the articulation constraints. We derive the equations of a Riemannian Extended Kalman Filter to perform the structure estimation from an image sequence captured by a perspective camera. In order to(More)
—Recovering 3D full-body human pose is a challenging problem with many applications. It has been successfully addressed by motion capture systems with body worn markers and multiple cameras. In this paper, we address the more challenging case of not only using a single camera but also not leveraging markers: going directly from 2D appearance to 3D geometry.(More)
— Data association is one of the fundamental problems in multi-sensor systems. Most current techniques rely on pairwise data associations which can be spurious even after the employment of outlier rejection schemes. Considering multiple pairwise associations at once significantly increases accuracy and leads to consistency. In this work, we propose two(More)
— This work addresses the problem of fusing two random vectors with unknown cross-correlations. We present a formulation and a numerical method for computing the optimal estimate in the minimax sense. We extend our formulation to linear measurement models that depend on two random vectors with unknown cross-correlations. As an application we consider the(More)
The trifocal tensor, which describes the relation between projections of points and lines in three views, is a fundamental entity of geometric computer vision. In this work, we investigate a new parametrization of the trifocal tensor for calibrated cameras with non-colinear pinholes obtained from a quotient Riemannian manifold. We incorporate this(More)
In this paper, we explore the exponential map and its inverse, the logarithm map, for the group SIM(n) of similarity transformations in &#x211D;<sup>n</sup> which are the composition of a rotation, a translation and a uniform scaling. We give a formula for the exponential map and we prove that it is surjective. We give an explicit formula for the case of n(More)