A comparison of local feature detectors and descriptors for visual object categorization by intra-class repeatability and matching

Intuitive and easily interpretable performance measures, repeatability and matching performance, for local feature detectors and descriptors were introduced by Mikolajczyk et al. [10, 9]. They, however, measured performance in a wide baseline setting that does not correspond to the visual object categorisation problem which is a popular application of the detectors and descriptors. The limitation has been recognised and ad hoc evaluations proposed. To the authors´ best knowledge, our work is the first which extends the original repeatability and matching performance measures to the case of object classes. Using the novel evaluation framework we test state-of-the-art detectors and descriptors with the popular Caltech-101 dataset and report the object category level (intra-class) repeatability and matching performances.