title: An algorithm for the contextual adaption of SURF octave selection with good matching performance: best octaves.
abstract: Speeded-Up Robust Features is a feature extraction algorithm designed for real-time execution, although this is rarely achievable on low-power hardware such as that in mobile robots. One way to reduce the computation is to discard some of the scale-space octaves, and previous research has simply discarded the higher octaves. This paper shows that this approach is not always the most sensible and presents an algorithm for choosing which octaves to discard based on the properties of the imagery. Results obtained with this best octaves algorithm show that it is able to achieve a significant reduction in computation without compromising matching performance.
authors.affiliation: School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK. sehsan@essex.ac.uk
authors.forename: Shoaib
authors.initials: S
authors.lastname: Ehsan
authors.forename: Nadia
authors.initials: N
authors.lastname: Kanwal
authors.forename: Adrian F
authors.initials: AF
authors.lastname: Clark
authors.forename: Klaus D
authors.initials: KD
authors.lastname: McDonald-Maier
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity