Indoor navigation and localization for visually impaired people using weighted topological map

Problem Statement: Image base methods are a new approach for solving problems of navigations for visually impaired people. Approach: The study introduced a new approach of an electronic cane for blind people using the environment represented as a weighted topological graph instead, each node contains images taken at some poses in the work space, instead of building a metric (3D) model of the environment. Results: By computing weights between already stored images and the real scene of the environment and take some considerations like sessions. The system gives advices for the blind person to select the right direction in indoor navigate depending on weights and session, where a mono camera cane-held gives information in front of the visually impaired person. Conclusion: A cane that has the ability of getting SIFT feature for an object or site from a sequence of live images using the suggested approach is very satisfactory, The session and weight, speed up the system and gives a wide range indoor navigation and may be used to outdoor. Experimental results demonstrated a good performance of proposed method, the identification of different scenes to the blind person done by constructing the weighted visual environment graph to the system. The proposed scheme is using SIFT features to represent the objects and the sites.

[1]  David Filliat,et al.  A visual bag of words method for interactive qualitative localization and mapping , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[2]  Paul Newman,et al.  Detecting Loop Closure with Scene Sequences , 2007, International Journal of Computer Vision.

[3]  Pietro Perona,et al.  A Bayesian hierarchical model for learning natural scene categories , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[4]  Thomas Ertl,et al.  Design and development of an indoor navigation and object identification system for the blind , 2003, ASSETS.

[5]  Juan D. Tardós,et al.  Data association in stochastic mapping using the joint compatibility test , 2001, IEEE Trans. Robotics Autom..

[6]  Óscar Martínez Mozos,et al.  Interest Point Detectors for Visual SLAM , 2007, CAEPIA.

[7]  Thomas Ertl,et al.  Augmented Indoor Modeling for Navigation Support for the Blind , 2005, CPSN.

[8]  Ben J. A. Kröse,et al.  Navigation using an appearance based topological map , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[9]  Elena Lazkano,et al.  Handle identification by keypoint extraction , 2007 .

[10]  Gabriela Csurka,et al.  Visual categorization with bags of keypoints , 2002, eccv 2004.

[11]  Ben Kröse,et al.  Image based navigation using a topological map , 2007 .

[12]  Thomas Ertl,et al.  Interactive tracking of movable objects for the blind on the basis of environment models and perception-oriented object recognition methods , 2006, Assets '06.

[13]  Ben Kröse,et al.  Pruning the image set for appearance based robot localization , 2005 .