Jean-Thierry Lapresté

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We present QUAFF, a new skeleton-based parallel programming library. Its main originality is to rely on C++ template meta-programming techniques to achieve high efficiency. In particular, by performing most of skeleton instantiation and optimization at compile-time, QUAFF can keep the overhead traditionally associated to object-oriented implementations of(More)
— The paper presents a method for estimating the inverse Jacobian matrix of a function, without computing the direct Jacobian matrix. The resulting inverse Jacobian matrix is shown to perform much better in modelling a relation θ = f −1 (x) than the classical Moore-Penrose inverse J + f. Theoretical insight as well as comparisons in the domain of visual(More)
This paper presents a new method that permits to solve the problem of determination of a modelled 3D-object spatial attitude from a single perspective image and to compute the covariance matrix associated to the attitude parameters. Its principle is based on the interpretation of at least three segments as the perspective projection of linear ridges of the(More)
Two basic facts motivate this paper: (1) particle filter based trackers have become increasingly powerful in recent years, and (2) object detectors using statistical learning algorithms often work at a near real-time rate. We present the use of classifiers as likelihood observation function of a particle filter. The original resulting method is able to(More)