Visual sequence-based place recognition for changing conditions and varied viewpoints

Pepperell, Edward (2016) Visual sequence-based place recognition for changing conditions and varied viewpoints. PhD by Publication, Queensland University of Technology.

Abstract

Correctly identifying previously-visited locations is essential for robotic place recognition and localisation. This thesis presents training-free solutions to vision-based place recognition under changing environmental conditions and camera viewpoints. Using vision as a primary sensor, the proposed approaches combine image segmentation and rescaling techniques over sequences of visual imagery to enable successful place recognition over a range of challenging environments where prior techniques have failed.

Impact and interest:

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44 since deposited on 05 Jul 2016
44 in the past twelve months

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ID Code: 93741
Item Type: QUT Thesis (PhD by Publication)
Supervisor: Milford, Michael & Corke, Peter
Additional Information: Recipient of the 2016 Outstanding Doctoral Thesis Award
Keywords: visual place recognition, navigation, appearance-based localisation, SeqSLAM, SMART, ODTA
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 05 Jul 2016 05:20
Last Modified: 13 Apr 2017 07:13

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