Obstacle detection using optical flow

Low, Toby & Wyeth, Gordon (2005) Obstacle detection using optical flow. In Sammut, Claude (Ed.) Proceedings of Australasian Conference on Robotics and Automation 2005, Australian Robotics and Automation Association Inc, Sydney, N.S.W.

View at publisher


Motion has been examined in biology to be a critical component for obstacle avoidance and navigation. In particular, optical flow is a powerful motion cue that has been exploited in many biological systems for survival. In this paper, we investigate an obstacle detection system that uses optical flow to obtain range information to objects. Our experimental results demonstrate that optical flow is capable of providing good obstacle information but has obvious failure modes. We acknowledge that our optical flow system has certain disadvantages and cannot be solely used for navigation. Instead, we believe that optical flow is a critical visual subsystem used when moving at reason- able speeds. When combined with other visual subsystems, considerable synergy can result.

Impact and interest:

22 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

341 since deposited on 23 Jun 2010
11 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 32838
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
ISBN: 0958758379
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Copyright Owner: Copyright 2005 [please consult the authors]
Deposited On: 23 Jun 2010 04:08
Last Modified: 10 Aug 2011 15:44

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page