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|Title:||Recent Trends in Emotion Analysis: A Big Data Analysis Perspective||Authors:||Ozyer T.
|Keywords:||Human activity recognition
skeleton based recognition
video based recognition
|Issue Date:||2020||Publisher:||Institute of Electrical and Electronics Engineers Inc.||Source:||12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020, 7 December 2020 through 10 December 2020, , 168050||Abstract:||Human action recognition has recently started to find its way into applications in different applications. Accordingly, human action recognition methods are becoming increasingly important in our daily life. They are used for different purposes such as automation, security, surveillance, health, smart home systems, and customer behaviour prediction, among others. Though have more systems with methods provides a rich pool of choices, it is important to well understand the performance of these systems and their success rates in recognizing the right activities in order to decide on the most appropriate system for the current application domain. This survey tackles this issue by analyzing and commenting on the available human action recognition systems and methods. © 2020 IEEE.||URI:||https://doi.org/10.1109/ASONAM49781.2020.9381441
|Appears in Collections:||Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering|
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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