Calibration par programmation linéaire et reconstruction spatio-temporelle à partir de réseaux d’images

Jérôme Courchay 1, 2
2 IMAGINE [Marne-la-Vallée]
LIGM - Laboratoire d'Informatique Gaspard-Monge, ENPC - École des Ponts ParisTech
Abstract : The issue of retrieving a 3D shape from a static scene captured with multiple view point calibrated cameras has been deeply studied these last decades. Results presented in the stereovision benchmark made by Strecha et al., show the high quality of state of the art methods. Particularly, works from IMAGINE laboratory lead to impressive results. So, it becomes convenient to calibrate wider and wider scenes, in order to apply these stereovision algorithms to large scale scenes. Three main objectives appear : – The calibration accuracy should be improved. As stated by Yasutaka Furukawa, even stereovision benchmarks use noisy cameras. So one obvious way to improve stereovision, is to improve camera calibration. – It is crucial to take cycles into account in cameras graph in a global way. Most of nowadays methods are sequential and so present a drift. So these methods do not offer the guarantee to retrieve the loopy configuration for a loop made of a high number of images, but retrieve a spiral configuration. As we aim to calibrate wider and wider cameras networks, this point becomes quite crucial. – To calibrate wide cameras networks, having quick and linear algorithms can be necessary. Calibration methods we propose in the first part, allow to calibrate with an accuracy close to state of the art. Moreover, we take cyclicity constraints into account in a global way, with linear optimisations under linear constraints. So these methods allow to take cycle into account and benefit from quickness of linear programming. Finally, sterovision being a well studied topic, it is convenient to concentrate on the next step, that is, spatio-temporal reconstruction. The IMAGINE' stereovision method being the state of the art, it is interesting to extend this method to spatio-temporal reconstruction, that is, dynamique scene reconstruction captured from a dome of cameras
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Jérôme Courchay. Calibration par programmation linéaire et reconstruction spatio-temporelle à partir de réseaux d’images. Autre [cs.OH]. Université Paris-Est, 2011. Français. ⟨NNT : 2011PEST1014⟩. ⟨pastel-00665070⟩

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