cultural heritage; machine learning; potsherds; computer vision; image categorization
Diego Jimenez-Badillo, Edgar Roman-Rangel (2016), Application of the ‘Bag of Words’ model (bow) for analysing archaeological potsherds, in CAA2015. Keep the Revolution Going. Proceedings of the 43rd. Annual Conference on Computer Applicati
, Siena, Italy.Archaeopres, Oxford.
Edgar Roman-Rangel, Diego Jimenez-Badillo, Stephane Marchand-Maillet (2016), Rotation Invariant Local Shape Descriptors for Classification of Archaeological 3D Model, in Proceedings of the 8th Mexican Conference on Pattern Recognition (MCPR)
, Guanajuato, MexicoLecture Notes in Computer Science (LNCS) - Springer, Switzerland.
Roman-Rangel Edgar, Wang Changhu, Marchand-Maillet Stephane (2016), SimMap: Similarity Maps for Scale Invariant Local Shape Descriptors, in Neurocomputing
, 175(B), 888-898.
Roman-Rangel Edgar, Jimenez-Badillo Diego (2015), Similarity Analysis of Archaeological Potsherds using 3D Surfaces, in 7th Mexican Conference on Pattern Recognition. Lecture Notes in Computer Science.
, Mexico City, Mexico.Lecture Notes in Computer Science (LNCS) - Springer., Switzerland..
Roman-Rangel Edgar, Marchand-Maillet Stephane (2014), Automatic Removal of Visual Stop-Words, in MM '14 Proceedings of the ACM International Conference on Multimedia
, Orlando, USA.ACM, New York.
Roman-Rangel Edgar, Jimenez-Badillo Diego, Aguayo-Ortiz Estibaliz (2014), Categorization of Aztec Potsherds using 3D Local Descriptors, in Computer Vision - ACCV 2014 Workshops
, Singapore Lecture Notes in Computer Science (LNCS) - Springer, Switzerland.
Edgar Roman-Rangel, Diego Jimenez-Badillo, Stephane Marchand-Maillet, Classification and Retrieval of Archaeological Potsherds using Histograms of Spherical Orientations, in ACM Journal on Computing and Cultural Heritage (JOCCH)
The Tepalcatl project will focus on advancing the state-of-the-art in computational archaeology. More precisely, this project will investigate the potential of using clustering and classification methods, that provide stable quantitive results, to address the problem of automatic categorization of potsherds, which often requires qualitative analysis and expert knowledge. On the one hand, the Tepalcatl project has the technical objective of advancing the state-of-the-art in methods for efficient clustering and classification of image collections. On the other hand, it will provide tools to assist archaeologists in the automatic categorization of potsherds. The importance of this research project lays upon the fact that potsherds are the most studied material in any excavation site, as they provide with the relevant knowledge regarding the cultural and historical context for a given site, thus their categorization is an important challenge that requires efficient tools that can be used at excavation sites. Overall, this work represents a bi-disciplinary effort towards bringing the potential that computer science methods have in providing tools to satisfy archaeological needs.