Towards a Hierarchical Multitask Classification Framework for Cultural Heritage

Abdelhak Belhi, Abdelaziz Bouras, Sebti Foufou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Digital technologies such as 3D imaging, data analytics and computer vision opened the door to a large set of applications in cultural heritage. Digital acquisition of a cultural assets takes nowadays a couple of seconds thanks to the achievements in 2D and 3D acquisition technologies. However, enriching these cultural assets with labels and relevant metadata is still not fully automatized especially due to their nature and specificities. With the recent publication of several cultural heritage datasets, many researchers are tackling the challenge of effectively classifying and annotating digital heritage. The challenges that are often addressed are related to visual recognition and image classification. In this paper, we present a novel approach of hierarchical classification for cultural heritage assets. The metadata structural differences that exist between cultural assets motivated us to design a classification framework that can efficiently perform the classification of multiple types of assets. Our approach relies on several deep learning classifiers, each of them is assigned the task of classifying a certain type of assets. The classification framework starts the labeling process by first determining the asset type. The asset is then assigned to a specific classifier in order to be annotated with data fields related to its type. As a preliminary step, we successfully designed a general cultural type classifier and a specific type classifier for paintings. Our approach is currently achieving interesting results and is set to be improved by the integration of more asset types.

Original languageEnglish (US)
Title of host publication2018 IEEE/ACS 15th International Conference on Computer Systems and Applications, AICCSA 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781538691205
DOIs
StatePublished - Jan 14 2019
Event15th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2018 - Aqaba, Jordan
Duration: Oct 28 2018Nov 1 2018

Publication series

NameProceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
Volume2018-November
ISSN (Print)2161-5322
ISSN (Electronic)2161-5330

Conference

Conference15th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2018
CountryJordan
CityAqaba
Period10/28/1811/1/18

Keywords

  • Convolutional Neural Networks
  • Cultural heritage
  • Digital heritage
  • Digital preservation
  • Multitask Classification

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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