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.

An evaluation of recent local image descriptors for real-world applications of image matching / Bellavia, Fabio; Colombo, Carlo. - ELETTRONICO. - (2019), pp. 0-0. (Intervento presentato al convegno 16th IAPR International Conference on Machine Vision Applications MVA 2019 tenutosi a Tokyo) [10.23919/MVA.2019.8757967].

An evaluation of recent local image descriptors for real-world applications of image matching

Bellavia, Fabio;Colombo, Carlo
2019

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.
2019
16th IAPR International Conference on Machine Vision Applications MVA 2019
16th IAPR International Conference on Machine Vision Applications MVA 2019
Tokyo
Bellavia, Fabio; Colombo, Carlo
File in questo prodotto:
File Dimensione Formato  
mva_2019.pdf

accesso aperto

Tipologia: Versione finale referata (Postprint, Accepted manuscript)
Licenza: Tutti i diritti riservati
Dimensione 203.04 kB
Formato Adobe PDF
203.04 kB Adobe PDF

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1150559
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 1
social impact