An Augmented Reality CBIR System Based on Multimedia Knowledge Graph and Deep Learning Techniques in Cultural Heritage

被引:1
作者
Rinaldi, Antonio M. [1 ]
Russo, Cristiano [1 ]
Tommasino, Cristian [1 ]
机构
[1] Univ Napoli Federico II, Dept Elect Engn & Informat Technol, Via Claudio 21, I-80125 Naples, Italy
关键词
augmented reality; deep learning; linked open data; knowledge graph; SITES;
D O I
10.3390/computers11120172
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In the last few years, the spreading of new technologies, such as augmented reality (AR), has been changing our way of life. Notably, AR technologies have different applications in the cultural heritage realm, improving available information for a user while visiting museums, art exhibits, or generally a city. Moreover, the spread of new and more powerful mobile devices jointly with virtual reality (VR) visors contributes to the spread of AR in cultural heritage. This work presents an augmented reality mobile system based on content-based image analysis techniques and linked open data to improve user knowledge about cultural heritage. In particular, we explore the uses of traditional feature extraction methods and a new way to extract them employing deep learning techniques. Furthermore, we conduct a rigorous experimental analysis to recognize the best method to extract accurate multimedia features for cultural heritage analysis. Eventually, experiments show that our approach achieves good results with respect to different standard measures.
引用
收藏
页数:12
相关论文
共 44 条
  • [1] Affleck Y.K.T.K.J, 2007, NEW HERITAGE NEW MED
  • [2] Angelopoulou A., 2012, Mobile Wireless Middleware, Operating Systems, and Applications, P15, DOI DOI 10.1007/978-3-642-30607-5_2
  • [3] [Anonymous], 1995, THESIS AUSTR NATL U
  • [4] Bastiaansen Marcel., 2019, Augmented Reality and Virtual Reality, P113
  • [5] The Semantic Web - A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities
    Berners-Lee, T
    Hendler, J
    Lassila, O
    [J]. SCIENTIFIC AMERICAN, 2001, 284 (05) : 34 - +
  • [6] Bres S., 2006, LOCALISATION AUGMENT, P1
  • [7] Candan H., 2001, ACM SIGKDD EXPLORATI, V3, P6, DOI DOI 10.1145/507533.507536
  • [8] Candan K.S., 2010, Data Management for Multimedia Retrieval
  • [9] An ontology-driven multimedia focused crawler based on linked open data and deep learning techniques
    Capuano, Andrea
    Rinaldi, Antonio M.
    Russo, Cristiano
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (11-12) : 7577 - 7598
  • [10] Chen Jing, 2011, IET International Communication Conference on Wireless Mobile and Computing (CCWMC 2011), P262, DOI 10.1049/cp.2011.0887