Cited By
View all- Torres CFried JManjunath B(2018)Healthcare Event and Activity LoggingIEEE Journal of Translational Engineering in Health and Medicine10.1109/JTEHM.2018.28633866(1-12)Online publication date: 2018
RAM: Role Representation and Identification from combined Appearance and Activity Maps
Pages 144 - 150
Abstract
This work introduces a multimodal multiview camera network for role identification and re-identification in an Intensive Care Unit (ICU) room, where identifying individuals is not permitted. The analysis challenges include imaging conditions such as medical isolation (where all visitors wear scrubs), poor and non-uniform illumination, or variable camera views. We propose a role representation, which combines static appearance features such as texture and color, together with a dynamic quantification of human locations and interactions that results in a semantic map. The proposed representation is easy to compute and robust to varying ICU conditions and network configurations, which make the methods suitable for low-power distributed sensor network deployment. Thorough evaluations and comparisons with competing methods are performed. The findings from this approach enable the compliant analysis of workflows in healthcare, while protecting the privacy of patients and medical staff.
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Index Terms
- RAM: Role Representation and Identification from combined Appearance and Activity Maps
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Published In
September 2017
221 pages
ISBN:9781450354875
DOI:10.1145/3131885
Copyright © 2017 ACM.
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- Stanford University: Stanford University
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New York, NY, United States
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Published: 05 September 2017
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ICDSC 2017
ICDSC 2017: International Conference on Distributed Smart Cameras
September 5 - 7, 2017
CA, Stanford, USA
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Overall Acceptance Rate 92 of 117 submissions, 79%
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View all- Torres CFried JManjunath B(2018)Healthcare Event and Activity LoggingIEEE Journal of Translational Engineering in Health and Medicine10.1109/JTEHM.2018.28633866(1-12)Online publication date: 2018
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