Strohmayer, J., & Kampel, M. (2023). Blind Modalities for Human Activity Recognition. In Assistive Technology: Shaping a Sustainable and Inclusive World (pp. 89–96). IOS Press, Incorporated. https://doi.org/10.3233/SHTI230601
Assistive Technology: Shaping a Sustainable and Inclusive World
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ISBN:
978-1-64368-422-2
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Date (published):
23-Aug-2023
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Event name:
17th International Conference of the Association for the Advancement of Assistive Technology in Europe (AAATE 2023)
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Event date:
30-Aug-2023 - 1-Sep-2023
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Event place:
Paris, France
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Number of Pages:
8
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Publisher:
IOS Press, Incorporated
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Peer reviewed:
Yes
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Keywords:
Humans; Automation; Neural Networks, Computer; Privacy; blind modalities; human activity recognition; person-centric sensing; Algorithms; Human Activities
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Abstract:
Human Activity Recognition (HAR) has attracted considerable interest due to its ability to facilitate automation in various application areas, including but not limited to smart homes, active assisted living, and security. At present, optical modalities such as RGB, depth, and thermal imaging are prevalent in the field due to the effectiveness of deep learning algorithms like Convolutional Neural Networks (CNNs) and the abundance of publicly available image data. However, unconventional modalities such as radar, WiFi, seismic and environmental sensors are emerging as potential alternatives due to their capacity for contactless long-range sensing in spatially constrained environments and preservation of visual privacy. This work gives an overview of the HAR modalities landscape and discusses works that apply these emerging modalities in new and unconventional ways to inform researchers and practitioners about challenges and opportunities in the field of HAR.
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Project title:
Privacy-Aware and Acceptable Video-Based Technologies and Services for Active and Assisted Living: 861091 (European Commission)
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Research Areas:
Visual Computing and Human-Centered Technology: 100%
