Authors:
Séverine Cloix
1
;
Viviana Weiss
2
;
Guido Bologna
2
;
Thierry Pun
2
and
David Hasler
3
Affiliations:
1
Vision Embedded Systems, CSEM SA and University of Geneva, Switzerland
;
2
University of Geneva, Switzerland
;
3
Vision Embedded Systems and CSEM SA, Switzerland
Keyword(s):
Binocular Stereo Vision, Sparse 3D Map, Obstacle Detection, Object Detection, Boosting, Elderly Care.
Abstract:
With the increasing proportion of senior citizens, many mobility aid devices have been developed such as the rollator. However, under some circumstances, the latter may cause accidents. The EyeWalker project aims to develop a small and autonomous device for rollators to help elderly people, especially those with some degree of visual impairment, avoiding common dangers like obstacles and hazardous ground changes, both outdoors and indoors. We propose a method of real-time stereo obstacle detection using sparse 3D information. Working with sparse 3D points, in opposition to dense 3D maps, is computationally more efficient and more appropriate for a long battery-life. In our approach, 3D data are extracted from a stereo-rig of two 2D high dynamic range cameras developed at the CSEM (Centre Suisse d'Electronique et de Microtechnique) and processed to perform a boosting classification. We also present a deformable 3D object detector for which the 3D points are combined in several differe
nt ways and result in a set of pose estimates used to execute a less ill-posed classification. The evaluation, carried out on real stereo images of obstacles described with both 2D and 3D features, shows promising results for a future use in real-world conditions.
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