Autors: Hristov, P. A., Nikolov, P. M., Manolova, A. H., Boumbarov, O. L.
Title: Multi-view RGB-D System for Person Specific Activity Recognition in the context of holographic communication
Keywords: Measurement, Solid modeling, Semantics, Activity recognition, Data models, Skeleton, Facial features

Abstract: Activity recognition is a key component of context-aware holographic communication to support optimal quality flow of data, but conventional approaches often lack in semantic information and context-awareness due to problems such as difficulty identifying the activity which the individiual performs; overfitting when building activity models; collection of a large amount of labeled data from each end user. This paper presents a fully developed multi-view RGB-D system based on user-specific metrics - facial features coupled with a body skeleton. The system employs a skeleton-based approach. We test the performance of the proposed architecture in a controlled environment.



    2020 XXIX International Scientific Conference Electronics (ET), 2020, Bulgaria, IEEE, DOI 10.1109/ET50336.2020.9238233

    Copyright IEEE

    Цитирания (Citation/s):
    1. Su, M., Zhang, C., Liu, Q., Liang, B., & Wang, J. (2021, October). Holographic communication technology. In 2021 International Conference on Neural Networks, Information and Communication Engineering (Vol. 11933, pp. 437-441). SPIE. - 2021 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus