Evaluation of Feature Detectors on Repeatability Quality of Facial Keypoints In Triangulation Method

Abstract

This study derived from a research focusing on 3D face recognition using ToF camera. But the system can't be used outdoors, because of a backlight. To solve this problem, a commercial digital single-lens reflex (DSLR) camera will be used. It can be approached y solving the stereo-view reconstruction problem for each pair of consecutive images. To reconstruct an object, projection matrix estimation from 2D point correspondences will be needed. The accuracy of 3D reconstruction is highly dependent on the corresponding points of 2D data projections from images to other images. In this research, The detectors are Harris-Stephens, SURF, FAST, Minimum Eigenvalue, and BRISK have been tested and analyzed through black box test. To evaluate feature detectors performance, the repeatability score for a given pair of images is computed. To do that it can use recall and precision. The best detector is the Harris Stephens detector because it has the best F-measure values of 0.46.