Person Identification with Visual Summary for a Safe Access to a Smart Home
Shahinur Alam, Mohammed Yeasin

TL;DR
This paper presents SafeAccess, a smart home system that uses real-time video analysis and facial recognition to identify individuals, enhance safety, and provide visual summaries for users, especially aiding those with disabilities.
Contribution
The paper introduces a robust recognition engine and a visual summary system tailored for smart homes, addressing real-world challenges like speed, accuracy, and environmental variability.
Findings
Achieved an average F-score of 0.97 in person identification.
Generated visual summaries with an average accuracy of 98.01%.
Successfully classified individuals into groups with high accuracy.
Abstract
SafeAccess is an integrated system designed to provide easier and safer access to a smart home for people with or without disabilities. The system is designed to enhance safety and promote the independence of people with disability (i.e., visually impaired). The key functionality of the system includes the detection and identification of human and generating contextual visual summary from the real-time video streams obtained from the cameras placed in strategic locations around the house. In addition, the system classifies human into groups (i.e. friends/families/caregiver versus intruders/burglars/unknown). These features allow the user to grant/deny remote access to the premises or ability to call emergency services. In this paper, we focus on designing a prototype system for the smart home and building a robust recognition engine that meets the system criteria and addresses speed,…
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Taxonomy
TopicsVideo Surveillance and Tracking Methods · Face recognition and analysis · IoT-based Smart Home Systems
