Stereo-based Aerial Obstacle Detection for the Visually Impaired

In this paper, we present a novel approach for aerial obstacle detection using a stereo vision wearable device in the context of the visually impaired assistance. This kind of obstacles are specially dangerous because they could not be detected by the walking stick. The algorithm maintains a local 3D map of the vicinity of the user, which is estimated through a 6DOF egomotion algorithm. The trajectory is used to predict the next movement of the blind and the 3D information of the local map is used to evaluate a possible aerial obstacles in the next pose. A key stabilization algorithm is introduced in order to maintain the floor of the map continuously aligned with the horizontal plane. This is a very important task, because in a wearable 3D device, the relative transformation of the camera reference system with respect to the user and the environment is continuously changed. In the experimental section, we show the results of the algorithm in several situations using real data.

[1]  Juan Manuel Sáez,et al.  6DOF entropy minimization SLAM , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[2]  Juan Manuel Sáez,et al.  First Steps towards Stereo-based 6DOF SLAM for the Visually Impaired , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[3]  James J. Little,et al.  Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks , 2002, Int. J. Robotics Res..

[4]  Nikos Komodakis,et al.  3D visual reconstruction of large scale natural sites and their fauna , 2005, Signal Process. Image Commun..

[5]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[6]  Haifeng Chen,et al.  Robust regression with projection based M-estimators , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[7]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[8]  Michael Brady,et al.  Stereo Vision-Based Obstacle Detection for Partially Sighted People , 1998, ACCV.

[9]  Alfred O. Hero,et al.  Asymptotic theory of greedy approximations to minimal k-point random graphs , 1999, IEEE Trans. Inf. Theory.

[10]  Clark F. Olson,et al.  Rover navigation using stereo ego-motion , 2003, Robotics Auton. Syst..

[11]  James M. Coughlan,et al.  Terrain Analysis for Blind Wheelchair Users: Computer Vision Algorithms for Finding Curbs and other Negative Obstacles , 2007, CVHI.

[12]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..