Detection of fast incoming objects with a moving camera
Fabio Poiesi and Andrea Cavallaro
Abstract
Using a monocular camera for early collision detection in cluttered scenes to elude fast incoming objects is a desirable but challenging functionality for mobile robots, such as small drones. We present a novel moving object detection and avoidance algorithm for an uncalibrated camera that uses only the optical flow to predict collisions. First, we estimate the optical flow and compensate the global camera motion. Then we detect incoming objects while removing the noise caused by dynamic textures, nearby terrain and lens distortion by means of an adaptively learnt background-motion model. Next, we estimate the time to contact, namely the expected time for an incoming object to cross the infinite plane defined by the extension of the image plane. Finally, we combine the time to contact and the compensated motion in a Bayesian framework to identify an object-free region the robot can move towards to avoid the collision. We demonstrate and evaluate the proposed algorithm using footage of flying robots that observe fast incoming objects such as birds, balls and other drones.
Session
Video events, robot vision and deep learning
Files
Extended Abstract (PDF, 397K)
Paper (PDF, 3M)
DOI
10.5244/C.30.146
https://dx.doi.org/10.5244/C.30.146
Citation
Fabio Poiesi and Andrea Cavallaro. Detection of fast incoming objects with a moving camera. In Richard C. Wilson, Edwin R. Hancock and William A. P. Smith, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 146.1-146.11. BMVA Press, September 2016.
Bibtex
@inproceedings{BMVC2016_146,
title={Detection of fast incoming objects with a moving camera},
author={Fabio Poiesi and Andrea Cavallaro},
year={2016},
month={September},
pages={146.1-146.11},
articleno={146},
numpages={11},
booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
publisher={BMVA Press},
editor={Richard C. Wilson, Edwin R. Hancock and William A. P. Smith},
doi={10.5244/C.30.146},
isbn={1-901725-59-6},
url={https://dx.doi.org/10.5244/C.30.146}
}