ICRA 2012 Paper Abstract


Paper TuC01.5

Hung, Calvin (University of Sydney), Bryson, Mitch (University of Sydney), Sukkarieh, Salah (University of Sydney)

"ShadowCut" - an Unsupervised Object Segmentation Algorithm for Aerial Robotic Surveillance Applications

Scheduled for presentation during the Regular Session "Autonomy and Vision for UAVs" (TuC01), Tuesday, May 15, 2012, 15:30−15:45, Meeting Room 1 (Mini-sota)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on May 21, 2018

Keywords Aerial Robotics, Field Robots, Recognition


This paper introduces an unsupervised graph cut based object segmentation algorithm, ShadowCut, for robotic aerial surveillance applications. By exploiting the spatial setting of the aerial imagery, ShadowCut algorithm differs from state-of-the-art object segmentation algorithms by not requiring a large number of labelled training data set, nor constant user interaction. In this paper it is shown that, by combining robotic navigation data and a shadow model, it is possible to provide these seed labels with a probabilistic sampling model for object segmentation in aerial imagery. Experiments were performed on aerial data sets consisting of data collected in outback Australia with an aerial robotic platform during an ecological surveillance mission, and aerial images with various natural targets from Google Earth. The segmentation results from the unsupervised ShadowCut algorithm are shown to be comparable with those from supervised graph cut algorithms.



Technical Content © IEEE Robotics & Automation Society

This site is protected by copyright and trademark laws under US and International law.
All rights reserved. © 2002-2018 PaperCept, Inc.
Page generated 2018-05-21  11:13:05 PST  Terms of use