ShadowCam: Real-Time Detection Of Moving Obstacles Behind A Corner For Autonomous Vehicles
Name
pub_2018_naser_shadowcam.pdf
Description
Paper
Size
2.57 MB
Format
Adobe PDF
Checksum (MD5)
15e2d5a21a529bb53ff2a5ffc739c3b1
Author(s)
Naser, Felix M
Gilitschenski, Igor
Rosman, Guy
Amini, Alexander A
Durand, Frederic
Torralba, Antonio
Wornell, Gregory W.
Freeman, William T
Karaman, Sertac
Rus, Daniela L
Date Issued
November 2018
Journal
21st IEEE International Conference on Intelligent Transportation Systems (ITSC 2018)
Publisher
IEEE
Citation
Naser, Felix et al. " ShadowCam: Real-Time Detection Of Moving Obstacles
Behind A Corner For Autonomous Vehicles." 21st IEEE International Conference on Intelligent Transportation Systems, 4-7 November, 2018, Maui, Hawaii, United States, IEEE, 2018.
Version
Author's final manuscript
Abstract
Moving obstacles occluded by corners are a potential source for collisions in mobile robotics applications such as autonomous vehicles. In this paper, we address the problem of anticipating such collisions by proposing a vision-based detection algorithm for obstacles which are outside of a vehicle’s
direct line of sight. Our method detects shadows of obstacles hidden around corners and automatically classifies these unseen obstacles as “dynamic” or “static”. We evaluate our proposed detection algorithm on real-world corners and a large variety of simulated environments to assess generalizability in different challenging surface and lighting conditions. The mean classification
accuracy on simulated data is around 80% and on realworld corners approximately 70%. Additionally, we integrate our detection system on a full-scale autonomous wheelchair and demonstrate its feasibility as an additional safety mechanism through real-world experiments. We release our real-timecapable implementation of the proposed ShadowCam algorithm
and the dataset containing simulated and real-world data under an open-source license
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://its.papercept.net/conferences/conferences/ITSC18/program/ITSC18_ContentListWeb_2.html
