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)
Is it possible to calibrate a camera in the air and then use the calibration results to infer a new calibration corresponding to the embedding of the camera in another fluid (possibly water)? This problem is dealt within the paper. It is important to avoid direct underwater calibration, as it is much more inconvenient for experiments than the usual (air)(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 realtime rate. We present the use of classifiers as likelihood observation function of a particle filter. The original resulting method is able to(More)
SIMD extensions have been a feature of choice for processor manufacturers for a couple of decades. Designed to exploit data parallelism in applications at the instruction level, these extensions still require a high level of expertise or the use of potentially fragile compiler support or vendor-specific libraries. While a large fraction of their theoretical(More)