Speed-up Feature Detector using Adaptive Accelerated Segment Test

Abstract

ABSTRACTImage matching using local features of an image patch is a primary stage for various higher level computer vision applications such as object recognition, motion tracking, simultaneous localization and mapping, stereo vision, and so on. A feature from accelerated segment test (FAST) has shown to be a superior feature detector in terms of computational speed. In our previous research, we presented a feature detector that improves the speed of FAST. In this study, we extend it to speed up it further. Experimental results on benchmark data-sets reveal that the new method speeds up FAST detector better than our previous detector with marginal improvement in repeatability score. A comprehensive review of related feature detectors is also provided to place our work in context.