3D tracking via body radio reflections
Fadel Adib,Zachary Kabelac,Dina Katabi,Robert C. Miller +3 more
- 02 Apr 2014
- pp 317-329
TL;DR: WiTrack bridges a gap between RF-based localization systems which locate a user through walls and occlusions, and human-computer interaction systems like Kinect, which can track a user without instrumenting her body, but require the user to stay within the direct line of sight of the device.
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Abstract: This paper introduces WiTrack, a system that tracks the 3D motion of a user from the radio signals reflected off her body. It works even if the person is occluded from the WiTrack device or in a different room. WiTrack does not require the user to carry any wireless device, yet its accuracy exceeds current RF localization systems, which require the user to hold a transceiver. Empirical measurements with a WiTrack prototype show that, on average, it localizes the center of a human body to within a median of 10 to 13 cm in the x and y dimensions, and 21 cm in the z dimension. It also provides coarse tracking of body parts, identifying the direction of a pointing hand with a median of 11.2°. WiTrack bridges a gap between RF-based localization systems which locate a user through walls and occlusions, and human-computer interaction systems like Kinect, which can track a user without instrumenting her body, but require the user to stay within the direct line of sight of the device.
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Citations
Widar3.0: Zero-Effort Cross-Domain Gesture Recognition With Wi-Fi
Yi Zhang,Yue Zheng,Kun Qian,Gui Yang Zhang,Yunhao Liu,Chenshu Wu,Zheng-Hui Yang +6 more
TL;DR: The key insight of Widar3.0 is to derive and extract domain-independent features of human gestures at the lower signal level, which represent unique kinetic characteristics of gestures and are irrespective of domains, and develops a one-fits-all general model that requires only one-time training but can adapt to different data domains.
98
Device free human activity and fall recognition using WiFi channel state information (CSI)
Neena Damodaran,Elis Haruni,Muyassar Kokhkharova,Jörg Schäfer +3 more
- 01 Mar 2020
TL;DR: It is shown that it is possible to characterize activities and/or human body presence with high accuracy and to count the number of people in a room based on the CSI-data, which is a first step towards detecting more complex social behavior and activities.
Position Tracking for Virtual Reality Using Commodity WiFi
Manikanta Kotaru,Sachin Katti +1 more
- 21 Jul 2017
TL;DR: WiCapture is presented, a novel approach which leverages commodity WiFi infrastructure, which is ubiquitous today, for tracking purposes, while providing much higher range, resistance to occlusion, ubiquity and ease of deployment.
Deep Learning Radar Design for Breathing and Fall Detection
TL;DR: A radar-based technique that detects breathing and other movements seamlessly, and can detect a fall after it has happened, i.e., even when the person is static, is demonstrated.
95
WiSpeed: A Statistical Electromagnetic Approach for Device-Free Indoor Speed Estimation
TL;DR: In this article, a universal low-complexity indoor speed estimation system leveraging radio signals, such as commercial WiFi, LTE, 5G, etc., which can work in both device-free and device-based situations is presented.
95
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