Publications by authors named "S M Shahriar Shahriar Nirjon"

Human sensing, motion trajectory estimation, and identification are central to a wide range of applications in many domains such as retail stores, surveillance, public safety, public address, smart homes and cities, and access control. Existing solutions either require facial recognition or installation and maintenance of multiple units, or they lack long-term re-identification capability. In this paper, we propose a novel system - called EyeFi- that combines WiFi and camera on a standalone device to overcome these limitations.

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This paper introduces SuperRF- which takes radio frequency (RF) signals from an off-the-shelf, low-cost, 77GHz mmWave radar and produces an enhanced 3D RF representation of a scene. SuperRF is useful in scenarios where camera and other types of sensors do not work, or not allowed due to privacy concerns, or their performance is impacted due to bad lighting conditions and occlusions, or an alternate RF sensing system like synthetic aperture radar (SAR) is too large, inconvenient, and costly. Applications of SuperRF includes navigation and planning of autonomous and semi-autonomous systems, human-robot interactions and social robotics, and elderly and/or patient monitoring in-home healthcare scenarios.

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The lack of adequate training data is one of the major hurdles in WiFi-based activity recognition systems. In this paper, we propose Wi-Fringe, which is a WiFi CSI-based device-free human gesture recognition system that recognizes gestures, i.e.

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