Computerized obstacle avoidance systems for the blind and visually impaired
Intelligent systems and technologies in rehabilitation engineering
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Autonomicity An Antidote for Complexity?
CSBW '05 Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference - Workshops
Traffic light recognition using image processing compared to learning processes
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Grayscale template-matching invariant to rotation, scale, translation, brightness and contrast
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
2D staircase detection using real adaboost
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Context-based indoor object detection as an aid to blind persons accessing unfamiliar environments
Proceedings of the international conference on Multimedia
Improving computer vision-based indoor wayfinding for blind persons with context information
ICCHP'10 Proceedings of the 12th international conference on Computers helping people with special needs
Computer vision-based door detection for accessibility of unfamiliar environments to blind persons
ICCHP'10 Proceedings of the 12th international conference on Computers helping people with special needs
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Indoor signage detection based on saliency map and bipartite graph matching
BIBMW '11 Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops
Detecting stairs and pedestrian crosswalks for the blind by RGBD camera
BIBMW '12 Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)
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A computer vision-based wayfinding and navigation aid can improve the mobility of blind and visually impaired people to travel independently. In this paper, we develop a new framework to detect and recognize stairs, pedestrian crosswalks, and traffic signals based on RGB-D (Red, Green, Blue, and Depth) images. Since both stairs and pedestrian crosswalks are featured by a group of parallel lines, we first apply Hough transform to extract the concurrent parallel lines based on the RGB (Red, Green, and Blue) channels. Then, the Depth channel is employed to recognize pedestrian crosswalks and stairs. The detected stairs are further identified as stairs going up (upstairs) and stairs going down (downstairs). The distance between the camera and stairs is also estimated for blind users. Furthermore, the traffic signs of pedestrian crosswalks are recognized. The detection and recognition results on our collected datasets demonstrate the effectiveness and efficiency of our proposed framework.