A self-calibration approach for optical long baseline interferometry imaging

Current optical interferometers are affected by unknown turbulent phases on each telescope. In the field of radio-interferometry, the self-calibration technique is a powerful tool to process interferometric data with missing phase information. This paper intends to revisit the application of self-calibration to Optical Long Baseline Interferometry (OLBI). We cast rigorously the OLBI data processing problem into the self-calibration framework and demonstrate the efficiency of the method on real astronomical OLBI dataset

Les établissements financiers et la protection des acquéreurs de logements

Le Besnerais M. Les établissements financiers et la protection des acquéreurs de logements. In: Droit et Ville, tome 5, 1978. I.E.J.U.C.-C.N.A.B. Dix ans après : la loi du 3 janvier 1967 et la protection de l'acquéreur immobilier. pp. 13-26

TRANSFER FUNCTION ESTIMATION FOR SPACEBORNE TELESCOPES

The on-orbit calibration of the transfer function (TF) of a spaceborne optical telescope is of paramount importance for the restoration of its recorded images. We propose a novel method based on a physical modeling of the TF and on the automatic extraction from the image of sub-images containing appropriate patterns such as step functions. A least-square criterion is computed with all the extracted subimages, and is minimized as a function of the unknowns, which are the TF parameters and the step parameters. Our simulation results validate the method and show a precise estimation of the full 2D TF. 1

Real-Time Mobile Object Detection Using Stereo

International audienceThis paper considers passive vision for robotics and focuses on devising a real-time process for moving object detection using a stereo rig. As several previous works, our method relies on the use of dense stereo and of optical flow. Observing that the main computational load of existing methods is related to the estimation of the optical flow, we propose to use a fast algorithm based on Lucas-Kanade's paradigm. We derive a new uncertainty model which explicitly takes into account all errors originating from each estimation step of the process. In contrast with most previous works, we describe a rigorous expansion of the error related to vision based ego-motion estimation. Finally, we present a comparative study of performance on the KITTI dataset, which demonstrates the effectiveness of the proposed approach

Multi-objective optimization of the induction machine with minimization of audible electromagnetic noise

Induction motors optimal design can involve many variables and objectives, and generally requires to make several trade-offs, especially when including the audible electromagnetic noise criterion beyond the usual performance criteria. Multiobjective optimization techniques based on Pareto optimality are useful to help us finding the most interesting solutions and decide which one(s) to adopt. However, it is not always easy to analyse the Pareto-optimal solutions obtained with such methods, especially when treating more than three objectives, and Pareto fronts may contain more data than we might think. This paper briefly describes an analytical model of the variable-speed squirrel-cage induction machine which computes both its performances and sound power level of electromagnetic origin. The model is then coupled to the Non-dominated Sorting Genetic Algorithm (NSGA-II) in order to perform global optimization with respect to several objectives (e.g. noise level, efficiency and material cost). Finally, an optimization problem is solved and analysed, and some useful visualization tools of the Pareto optimal solutions and their characteristics are presented

Hand segmentation using a chromatic 3D camera

In this paper we present a new approach for hand shape segmentation using a passive monocular 3D camera. The camera depth estimation is based on the Depth from Defocus principle improved with the use of enhanced chromatic aberration. As this camera is passive and monocular, it can be used for indoor and outdoor application on a compact device, in contrast with active IR depth sensors that can be disturbed with the sun’s infrared illumination. We show on various experimental examples that hand can be segmented using a depth cue from the proposed 3D camera

3DSCAN: Online Ego-Localization and Environment Mapping for Micro Aerial Vehicles

International audienceWe present 3DSCAN (3D Scene Characterization for Autonomous Navigation), a software application for state estimation and environment modeling using lowcost 3D sensors, such as a stereorig and RGBD cameras. For state estimation, we describe an original keyframe-based stereoscopic visual odometry technique, which can run at more than 20Hz on a lightweight computer. This so-called ‘efficient Visual Odometry’ (eVO) has been evaluated on several datasets and provides accurate results and limited drift, even for indoor/outdoor trajectories. Environment modeling aggregates instantaneous depthmaps in a volumetric Octomap [15] representation. Stereoscopic depthmaps are computed by a very fast dense matching algorithm derived from eFolki, an optical flow code implemented on GPU. These developments are combined in the 3DSCAN software, which is successfully demonstrated on our MAV (Micro Aerial Vehicle) system, following indoor, outdoor or mixed trajectories

Advanced Imaging Methods for Long-Baseline Optical Interferometry

International audienc