Several image mosaicing algorithms claiming to advance the state of the art have been proposed so far. Though sometimes improvements can be recognised without quantitative evidences, the importance of a principled methodology to compare different algorithms is essential as this discipline evolves. Which is the best? What means the best? How to ascertain the supremacy? To answer such questions, in this paper we propose an evaluation methodology including standard data sets, ground-truth information and performance metrics. We also compare three variants of a well-known mosaicing algorithm according to the proposed methodology.
An Evaluation Methodology for Image Mosaicing Algorithms / P. Azzari; L. Di Stefano; S. Mattoccia. - STAMPA. - (2008), pp. 89-100. (Intervento presentato al convegno Advanced Concepts for Intelligent Vision Systems tenutosi a Juan les Pins, Francia nel 20-24 Ottobre 2008).
An Evaluation Methodology for Image Mosaicing Algorithms
AZZARI, PIETRO;DI STEFANO, LUIGI;MATTOCCIA, STEFANO
2008
Abstract
Several image mosaicing algorithms claiming to advance the state of the art have been proposed so far. Though sometimes improvements can be recognised without quantitative evidences, the importance of a principled methodology to compare different algorithms is essential as this discipline evolves. Which is the best? What means the best? How to ascertain the supremacy? To answer such questions, in this paper we propose an evaluation methodology including standard data sets, ground-truth information and performance metrics. We also compare three variants of a well-known mosaicing algorithm according to the proposed methodology.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
