Collision Detection for Visually Impaired from a Body-Mounted Camera
Abstract
A real-time collision detection system using a body-mounted camera is developed for visually impaired and blind people. The system computes sparse optical flow in the acquired videos, compensates for camera self-rotation using external gyro-sensor, and estimates collision risk in local image regions based on the motion estimates. Experimental results for a variety of scenarios involving static and dynamic obstacles are shown in terms of time-to-collision and obstacle localization in test videos. The proposed approach is successful in estimating collision risk for head-on obstacles as well as obstacles that are close to the walking paths of the user. An end-to-end collision warning system based on inputs from a video camera as well as a gyro-sensor has been implemented on a generic laptop and on an embedded OMAP-3 compatible platform. The proposed embedded system represents a valuable contribution toward the development of a portable vision aid for visually impaired and blind patients.
Cite
Text
Pundlik et al. "Collision Detection for Visually Impaired from a Body-Mounted Camera." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2013. doi:10.1109/CVPRW.2013.11Markdown
[Pundlik et al. "Collision Detection for Visually Impaired from a Body-Mounted Camera." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2013.](https://mlanthology.org/cvprw/2013/pundlik2013cvprw-collision/) doi:10.1109/CVPRW.2013.11BibTeX
@inproceedings{pundlik2013cvprw-collision,
title = {{Collision Detection for Visually Impaired from a Body-Mounted Camera}},
author = {Pundlik, Shrinivas J. and Tomasi, Matteo and Luo, Gang},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2013},
pages = {41-47},
doi = {10.1109/CVPRW.2013.11},
url = {https://mlanthology.org/cvprw/2013/pundlik2013cvprw-collision/}
}