Abstract
The skills required by machines in the last decade have grown exponentially. Recent efforts made by the scientific community have shown amazing results in the field of research related to artificial intelligence and robotics. Recent studies show that machines may be superior to humans in carrying out certain tasks. However, in many approaches they still fail to achieve high-level skills required to support humans and interact with them. Furthermore, the “intelligence” exhibited is hardly ever the result of a real autonomous decision. In this article we propose a novel approach, with the aim of providing a machine with the ability to evolve and build its own knowledge by combining both semantic and visual information. The proposed concept, its implementation and experimental results are shown and discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bülthoff, H.H., Wallraven, C., Giese, M.A.: Perceptual robotics. In: Siciliano, B., Khatib, O. (eds.) Springer Handbook of Robotics, pp. 1481–1498. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-30301-5_64
Caldarola, E.G., Rinaldi, A.M.: An approach to ontology integration for ontology reuse. In: 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI), pp. 384–393. IEEE (2016)
Chella, A., Lanza, F., Pipitone, A., Seidita, V.: Knowledge acquisition through introspection in human-robot cooperation. Biol. Inspired Cogn. Arch. 25, 1–7 (2018)
Fan, J., Luo, H., Gao, Y.: Learning the semantics of images by using unlabeled samples. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 2, pp. 704–710. IEEE (2005)
Lieto, A., Bhatt, M., Oltramari, A., Vernon, D.: The role of cognitive architectures in general artificial intelligence (2018)
Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)
Nöth, E., et al.: An integrated model of acoustics and language using semantic classification trees (1996)
Ramík, D.M., Madani, K., Sabourin, C.: From visual patterns to semantic description: a cognitive approach using artificial curiosity as the foundation. Pattern Recognit. Lett. 34(14), 1577–1588 (2013)
Ramík, D.M., Sabourin, C., Madani, K.: Autonomous knowledge acquisition based on artificial curiosity: application to mobile robots in an indoor environment. Robot. Auton. Syst. 61(12), 1680–1695 (2013)
Ramík, D.M., Sabourin, C., Moreno, R., Madani, K.: A machine learning based intelligent vision system for autonomous object detection and recognition. Appl. Intell. 40(2), 358–375 (2014)
Rinaldi, A.M.: A multimedia ontology model based on linguistic properties and audio-visual features. Inf. Sci. 277, 234–246 (2014)
Rinaldi, A.M.: A complete framework to manage multimedia ontologies in digital ecosystems. Int. J. Bus. Process. Integr. Manag. 7(4), 274–288 (2015)
Rinaldi, A.M., Russo, C.: A matching framework for multimedia data integration using semantics and ontologies. In: 2018 IEEE 12th International Conference on Semantic Computing (ICSC), pp. 363–368. IEEE (2018)
Rinaldi, A.M., Russo, C.: A semantic-based model to represent multimedia big data. In: Proceedings of the 10th International Conference on Management of Digital EcoSystems, pp. 31–38. ACM (2018)
Rinaldi, A.M., Russo, C.: User-centered information retrieval using semantic multimedia big data. In: 2018 IEEE International Conference on Big Data (Big Data), pp. 2304–2313. IEEE (2018)
Taniguchi, A., Taniguchi, T., Inamura, T.: Spatial concept acquisition for a mobile robot that integrates self-localization and unsupervised word discovery from spoken sentences. IEEE Trans. Cogn. Dev. Syst. 8(4), 285–297 (2016)
Vanzo, A., Part, J.L., Yu, Y., Nardi, D., Lemon, O.: Incrementally learning semantic attributes through dialogue interaction. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, pp. 865–873. International Foundation for Autonomous Agents and Multiagent Systems (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Russo, C., Madani, K., Rinaldi, A.M. (2019). Knowledge Construction Through Semantic Interpretation of Visual Information. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2019. Lecture Notes in Computer Science(), vol 11507. Springer, Cham. https://doi.org/10.1007/978-3-030-20518-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-030-20518-8_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-20517-1
Online ISBN: 978-3-030-20518-8
eBook Packages: Computer ScienceComputer Science (R0)