An evaluation of recent local image descriptors for real-world applications of image matching
- Autori: Bellavia F.; Colombo C.
- Anno di pubblicazione: 2019
- Tipologia: Contributo in atti di convegno pubblicato in volume
- OA Link: http://hdl.handle.net/10447/385505
Abstract
This paper discusses and compares the best and most recent local descriptors, evaluating them on increasingly complex image matching tasks, encompassing planar and non-planar scenarios under severe viewpoint changes. This evaluation, aimed at assessing descriptor suitability for real-world applications, leverages the concept of approximated overlap error as a means to naturally extend to non-planar scenes the standard metric used for planar scenes. According to the evaluation results, most descriptors exhibit a gradual performance degradation in the transition from planar to non-planar scenes. The best descriptors are those capable of capturing well not only the local image context, but also the global scene structure. Data-driven approaches are shown to have reached the matching robustness and accuracy of the best hand-crafted descriptors