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 x 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.
ACT-CORNER: Active Corner Finding for Optic Flow Determination
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IEEE Computer Society Press, Loa Alamitos [CA], USA
Proceeding of the IEEE International Conference on Robotics and Automation (ICRA), pp. 4679–4684. Loa Alamitos [CA]: IEEE Computer Society Press, 2013