Live metric 3D reconstruction on mobile phones
Proceedings of the IEEE International Conference on Computer Vision, 2013•cv-foundation.org
In this paper, we propose a complete on-device 3D reconstruction pipeline for mobile
monocular hand-held devices, which generates dense 3D models with absolute scale on-
site while simultaneously supplying the user with real-time interactive feedback. The method
fills a gap in current cloud-based mobile reconstruction services as it ensures at capture time
that the acquired image set fulfills desired quality and completeness criteria. In contrast to
existing systems, the developed framework offers multiple innovative solutions. In particular …
monocular hand-held devices, which generates dense 3D models with absolute scale on-
site while simultaneously supplying the user with real-time interactive feedback. The method
fills a gap in current cloud-based mobile reconstruction services as it ensures at capture time
that the acquired image set fulfills desired quality and completeness criteria. In contrast to
existing systems, the developed framework offers multiple innovative solutions. In particular …
Abstract
In this paper, we propose a complete on-device 3D reconstruction pipeline for mobile monocular hand-held devices, which generates dense 3D models with absolute scale on-site while simultaneously supplying the user with real-time interactive feedback. The method fills a gap in current cloud-based mobile reconstruction services as it ensures at capture time that the acquired image set fulfills desired quality and completeness criteria. In contrast to existing systems, the developed framework offers multiple innovative solutions. In particular, we investigate the usability of the available on-device inertial sensors to make the tracking and mapping process more resilient to rapid motions and to estimate the metric scale of the captured scene. Moreover, we propose an efficient and accurate sceme for dense stereo matching which allows to reduce the processing time to interaction speed. We demonstrate the performance of the reconstruction pipeline on multiple challenging indoor and outdoor scenes of different size and depth variability.
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