Abstract
In-Depth Evaluation of Popular Interest Point Detectors on Video Streams
by: Steffen Gauglitz and Tobias Höllerer
Abstract:
We present and in-depth evaluation of popular interest point detectors, which, in contrast to existing evaluations, is targeted towards the application in visual tracking and augmented reality. In particular, candidate algorithms, testbed, and performance criteria are chosen with respect to the application of visual tracking. We evaluate the impact of individual algorithm parameters and present results in terms of repeatability, number of features detected, and computation time. We also describe our method to semi-automatically generate ground truth in detail.
Keywords:
Computer Vision, Tracking, Evaluation, Repeatability, Corner Detectors, Features, Harris, Shi-Tomasi, Difference-of-Gaussian, Fast Hessian, FAST
Date:
May 2009
Document: 2009-08
