A Study of feature extraction algorithms for optical flow tracking
Nourani-Vatani, Navid, Borges, Paulo V. K., & Roberts, Jonathan M. (2012) A Study of feature extraction algorithms for optical flow tracking. In Australasian Conference on Robotics and Automation,, Australian Robotics and Automation Association, Victoria University of Wellington, New Zealand.
Sparse optical flow algorithms, such as the Lucas-Kanade approach, provide more robustness to noise than dense optical flow algorithms and are the preferred approach in many scenarios. Sparse optical flow algorithms estimate the displacement for a selected number of pixels in the image. These pixels can be chosen randomly. However, pixels in regions with more variance between the neighbours will produce more reliable displacement estimates. The selected pixel locations should therefore be chosen wisely. In this study, the suitability of Harris corners, Shi-Tomasi's “Good features to track", SIFT and SURF interest point extractors, Canny edges, and random pixel selection for the purpose of frame-by-frame tracking using a pyramidical Lucas-Kanade algorithm is investigated. The evaluation considers the important factors of processing time, feature count, and feature trackability in indoor and outdoor scenarios using ground vehicles and unmanned aerial vehicles, and for the purpose of visual odometry estimation.
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|Item Type:||Conference Paper|
|Keywords:||Optical Flow Tracking, Feature Extraction Algorithms|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Photodetectors Optical Sensors and Solar Cells (090605)
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Deposited On:||29 Aug 2014 07:04|
|Last Modified:||12 Sep 2014 04:18|
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