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dc.contributor.author Alam, Shahinur en
dc.contributor.author Mahmud, Md Sultan en
dc.contributor.author Yeasin, Mohammed en
dc.date.accessioned 2020-05-26T19:10:56Z
dc.date.available 2020-05-26T19:10:56Z
dc.date.issued 2020 en
dc.identifier.citation Journal on Technology and Persons with Disabilities 8: 267-288. en
dc.identifier.issn 2330-4219 en
dc.identifier.uri http://hdl.handle.net/10211.3/215993 en
dc.description 35th Annual Assistive Technology Conference Scientific/Research Proceedings, San Diego, 2020 en
dc.description.abstract An assistive solution to assess incoming threats (e.g., robbery, burglary, gun violence) for homes will enhance the safety of the people with or without disabilities. This paper presents 'SafeNet' - an integrated assistive system to generate context-oriented image descriptions to assess incoming threats. The key functionality of the system includes the detection and identification of human and generating image descriptions from the real-time video streams obtained from the cameras placed in strategic locations around the house. In this paper, we focus on developing a robust model called 'SafeNet' to generate image descriptions. To interact with the system, we implemented a dialog enabled interface for creating a personalized profile from face images or videos of friends/families. To improve computational efficiency, we apply change detection to filter out frames that do not have any activity and use Faster-RCNN to detect the human presence and extract faces using Multitask Cascaded Convolutional Networks (MTCNN). Subsequently, we apply LBP/FaceNet to identify a person. SafeNet sends image descriptions to the users with an MMS containing a person's name if any match found or as "Unknown", scene image, facial description, and contextual information. SafeNet identifies friends/families/caregiver versus intruders/unknown with an average F-score 0.97 and generates image descriptions from 10 classes with an average F-measure 0.97. en
dc.format application/pdf en
dc.format.extent 22 pages en
dc.language.iso en en
dc.publisher California State University, Northridge. en
dc.rights Copyright 2020 by the authors and California State University, Northridge en
dc.subject Assistive Solution en
dc.subject Home Safety en
dc.subject Independent living en
dc.title An Assistive Solution to Assess Incoming Threats for Homes en
dc.type Article en
dc.rights.license Creative Commons Attribution-NoDerivs 4.0 Unported License. en


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