Automated evaluation of interest point detectors

Abstract

Interest point detectors are important components in a variety of computer vision systems. This paper demonstrates an automated virtual 3D environment for controlling and measuring detected interest points on 2D images in an accurate and rapid manner. Real-time affine transform tools enable easy implementation and full automation of complex scene evaluations without the time-cost of a manual setup. Nine detectors are tested and compared using evaluation and testing methods based on Schmid [18]. Each detector is tested on the BSDS500 image set using rotation in the X, Y, and Z axis as well as scale in the X, Y axis. Results demonstrate the differing performance and behaviour of each detector across the evaluated transformations, which may assist computer vision practitioners in choosing the right detector for their application.