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Wright State University

1. Angeleas, Anargyros. A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction.

Degree: PhD, Computer Science and Engineering PhD, 2018, Wright State University

Human Activity Recognition is an actively researched domain for the past fewdecades, and is one of the most eminent applications of today. It is already part of our life,but due to high level of uncertainty and challenges of human detection, we have onlyapplication specific solutions. Thus, the problem being very demanding and still remainsunsolved.Within this PhD we delve into the problem, and approach it from a variety of viewpoints.At start, we present and evaluate different architectures and frameworks for activityrecognition.Henceforward, the focal point of our attention is automatic human activityrecognition. We conducted and present a survey that compares, categorizes, and evaluatesresearch surveys and reviews into four categories.Then a novel fully automatic view-independent multi-formal languagescollaborative scheme is presented for complex activity and emotion recognition, which isthe main contribution of this dissertation.We propose a collaborative three formal-languages, that is responsible for parsingmanipulating, and understanding all the data needed. Artificial Neural Networks are usedto classify an action primitive (simple activity), as well as to define change of activity.Finally, we capitalize the advantages of Fuzzy Cognitive Maps, and Rule-Based ColoredPetri-Nets to be able to classify a sequence of activities as normal or ab-normal. Advisors/Committee Members: Bourbakis, Nikolaos (Advisor).

Subjects/Keywords: Computer Science; Human Activity Recognition

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APA (6th Edition):

Angeleas, A. (2018). A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1526984767684238

Chicago Manual of Style (16th Edition):

Angeleas, Anargyros. “A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction.” 2018. Doctoral Dissertation, Wright State University. Accessed June 23, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1526984767684238.

MLA Handbook (7th Edition):

Angeleas, Anargyros. “A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction.” 2018. Web. 23 Jun 2018.

Vancouver:

Angeleas A. A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction. [Internet] [Doctoral dissertation]. Wright State University; 2018. [cited 2018 Jun 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1526984767684238.

Council of Science Editors:

Angeleas A. A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction. [Doctoral Dissertation]. Wright State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1526984767684238

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