Skip navigation
Skip navigation

Real Time Biologically-Inspired Depth Maps from Spherical Flow

McCarthy , Christopher; Barnes, Nick; Srinivasan, Mandyam V

Description

We present a strategy for generating real-time relative depth maps of an environment from optical flow, under general motion. We achieve this using an insect-inspired hemispherical fish-eye sensor with 190 degree FOV, and a derotated optical flow field. The de-rotation algorithm applied is based on the theoretical work of Nelson and Aloimonos [10]. From this we obtain the translational component of motion, and construct full relative depth maps on the sphere. We examine the robustness of this...[Show more]

dc.contributor.authorMcCarthy , Christopher
dc.contributor.authorBarnes, Nick
dc.contributor.authorSrinivasan, Mandyam V
dc.coverage.spatialRome Italy
dc.date.accessioned2015-12-07T22:44:04Z
dc.date.createdApril 10-14 2007
dc.identifier.isbn1424406021
dc.identifier.urihttp://hdl.handle.net/1885/25045
dc.description.abstractWe present a strategy for generating real-time relative depth maps of an environment from optical flow, under general motion. We achieve this using an insect-inspired hemispherical fish-eye sensor with 190 degree FOV, and a derotated optical flow field. The de-rotation algorithm applied is based on the theoretical work of Nelson and Aloimonos [10]. From this we obtain the translational component of motion, and construct full relative depth maps on the sphere. We examine the robustness of this strategy in both simulation and realworld experiments, for a variety of environmental scenarios. To our knowledge, this is the first demonstrated implementation of the Nelson and Aloimonos algorithm working in real-time, over real image sequences. In addition, we apply this algorithm to the real-time recovery of full relative depth maps. These preliminary results demonstrate the feasibility of this approach for closed-loop control of a robot.
dc.publisherOmniPress
dc.relation.ispartofseriesIEEE International Conference on Robotics and Automation (ICRA 2007)
dc.sourceProceedings of ICRA '07
dc.subjectKeywords: Aloimonos algorithm; Optical flow field; Spherical flow; Algorithms; Intelligent robots; Optical flows; Sensors; Strategic planning; Virtual reality; Real time systems
dc.titleReal Time Biologically-Inspired Depth Maps from Spherical Flow
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2007
local.identifier.absfor080104 - Computer Vision
local.identifier.ariespublicationu3594520xPUB36
local.type.statusPublished Version
local.contributor.affiliationMcCarthy , Christopher, College of Engineering and Computer Science, ANU
local.contributor.affiliationBarnes, Nick, College of Engineering and Computer Science, ANU
local.contributor.affiliationSrinivasan, Mandyam V, College of Medicine, Biology and Environment, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage4887
local.bibliographicCitation.lastpage4892
local.identifier.doi10.1109/ROBOT.2007.364232
dc.date.updated2015-12-07T11:20:48Z
local.identifier.scopusID2-s2.0-36349010843
CollectionsANU Research Publications

Download

File Description SizeFormat Image
01_McCarthy _Real_Time_2007.pdf499.68 kBAdobe PDF    Request a copy
02_McCarthy _Real_Time_2007.pdf63.3 kBAdobe PDF    Request a copy
03_McCarthy _Real_Time_2007.pdf1.98 MBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  22 January 2019/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator