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Building an Understanding of Human Activities in First Person Video using Fuzzy Inference

Schneider, Bradley A.
http://orcid.org/0000-0003-3059-8288
http://rave.ohiolink.edu/etdc/view?acc_num=wright1647342586221469

Abstract Details

2022, Doctor of Philosophy (PhD), Wright State University, Computer Science and Engineering PhD.
Activities of Daily Living (ADL’s) are the activities that people perform every day in their home as part of their typical routine. The in-home, automated monitoring of ADL’s has broad utility for intelligent systems that enable independent living for the elderly and mentally or physically disabled individuals. With rising interest in electronic health (e-Health) and mobile health (m-Health) technology, opportunities abound for the integration of activity monitoring systems into these newer forms of healthcare. In this dissertation we propose a novel system for describing ’s based on video collected from a wearable camera. Most in-home activities are naturally defined by interaction with objects. We leverage these object-centric activity definitions to develop a set of rules for a Fuzzy Inference System (FIS) that uses video features and the identification of objects to identify and classify activities. Further, we demonstrate that the use of FIS enhances the reliability of the system and provides enhanced explainability and interpretability of results over popular machine-learning classifiers due to the linguistic nature of fuzzy systems.
Tanvi Banerjee, Ph.D. (Advisor)
Yong Pei, Ph.D. (Committee Member)
Michael Riley, Ph.D. (Committee Member)
Mateen Rizki, Ph.D. (Committee Member)
Thomas Wischgoll, Ph.D. (Committee Member)
105 p.
Computer Science
human activities; activity recognition; activity classification; fuzzy logic; computer vision; object segmentation; fuzzy system; hand detection; activities of daily living;

Recommended Citations

Citations

  • Schneider, B. A. (2022). Building an Understanding of Human Activities in First Person Video using Fuzzy Inference [Doctoral dissertation, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1647342586221469

    APA Style (7th edition)

  • Schneider, Bradley. Building an Understanding of Human Activities in First Person Video using Fuzzy Inference. 2022. Wright State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1647342586221469.

    MLA Style (8th edition)

  • Schneider, Bradley. "Building an Understanding of Human Activities in First Person Video using Fuzzy Inference." Doctoral dissertation, Wright State University, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=wright1647342586221469

    Chicago Manual of Style (17th edition)

wright1647342586221469
116
© 2022, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.