Feature Evaluation with High-Resolution Images

The extraction of scale invariant image features is a fundamental task for many computer vision applications. Features are localized in the scale space of the image. A descriptor is build for each feature which is used to determine the correspondence to a second feature, usually extracted from a second image. For the evaluation of detectors and descriptors, benchmark image sets are used. The benchmarks consist of image sequences and homographies which determine the ground truth for the mapping between the images. The repeatability criterion evaluates the detection accuracy of the detectors while precision and recall measure the quality of the descriptors.