On the use of optical flow for scene change detection and description

Nourani-Vatani, Navid, Borges, Paulo V.K., Roberts, Jonathan M., & Srinivasan, Mandyam V. (2014) On the use of optical flow for scene change detection and description. Journal of Intelligent & Robotic Systems, 74(3-4), pp. 817-846.

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Abstract

We propose the use of optical flow information as a method for detecting and describing changes in the environment, from the perspective of a mobile camera. We analyze the characteristics of the optical flow signal and demonstrate how robust flow vectors can be generated and used for the detection of depth discontinuities and appearance changes at key locations. To successfully achieve this task, a full discussion on camera positioning, distortion compensation, noise filtering, and parameter estimation is presented. We then extract statistical attributes from the flow signal to describe the location of the scene changes. We also employ clustering and dominant shape of vectors to increase the descriptiveness. Once a database of nodes (where a node is a detected scene change) and their corresponding flow features is created, matching can be performed whenever nodes are encountered, such that topological localization can be achieved. We retrieve the most likely node according to the Mahalanobis and Chi-square distances between the current frame and the database. The results illustrate the applicability of the technique for detecting and describing scene changes in diverse lighting conditions, considering indoor and outdoor environments and different robot platforms.

Impact and interest:

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2 citations in Web of Science®

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ID Code: 82186
Item Type: Journal Article
Refereed: Yes
Additional Information: This work is funded jointly by the Australian government through the SIEF Postdoctoral Fellowship and the Endeavour IPRS scheme, the University of Queensland, the CSIRO ICT
Centre, the ARC Centre of Excellence in Vision Science (grant CE0561903), and a Queensland Smart State Premier’s Fellowship.
Keywords: Scene change detection, Optical flow descriptor, Mapping and localization, Computer vision, Mobile robots
DOI: 10.1007/s10846-013-9840-8
ISSN: 1573-0409
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2014 Springer Netherlands
Deposited On: 04 Mar 2015 23:56
Last Modified: 05 Mar 2015 21:25

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