ACT-CORNER: Active corner finding for optic flow determination

Author

de Croon, G.C.H.E. ; Nolfi, Stefano

Author_Institution

Micro Air Vehicle Lab., Delft Univ. of Technol., Delft, Netherlands

fYear

2013

fDate

6-10 May 2013

Firstpage

4679

Lastpage

4684

Abstract

A highly efficient corner finding algorithm, named ACT-CORNER, is introduced. The algorithm uses active sub-sampling: it searches for corners by exploiting information from local image samples. ACT-CORNER is compared to both the Harris and FAST corner detectors. It is computationally much more efficient than the Harris corner detector. The comparison with FAST depends on the image size, with an advantage for ACT-CORNER for image dimensions of 320 × 240 pixels or larger. ACT-CORNER´s performance is evaluated in the context of optic flow based Time-To-Contact (TTC) estimation. Image zoom experiments show that the accuracy of TTC estimations is similar when ACT-CORNER or FAST are used for corner detection. Finally, experiments with a Parrot AR drone show that the TTC estimates based on ACT-CORNER correspond well to sonar-based estimates.

Keywords

edge detection; image resolution; image sampling; image sequences; robot vision; ACT-CORNER performance evaluation; FAST corner detectors; Harris corner detectors; Parrot AR drone; TTC estimation; active corner finding algorithm; active subsampling; image dimensions; image zoom experiments; local image samples; optic flow based time-to-contact estimation; optic flow determination; sonar-based estimates; Cameras; Estimation; Integrated optics; Neurons; Optical filters; Optical imaging; Optical sensors;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation (ICRA), 2013 IEEE International Conference on

Conference_Location

Karlsruhe

ISSN

1050-4729

Print_ISBN

978-1-4673-5641-1

Type

conf

DOI

10.1109/ICRA.2013.6631243

Filename

6631243