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Home ยป WiDeo: Fine-grained Device-free Motion Tracing using RF Backscatter
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WiDeo: Fine-grained Device-free Motion Tracing using RF Backscatter

Authors: 

Kiran Joshi, Dinesh Bharadia, Manikanta Kotaru, and Sachin Katti, Stanford University

Abstract: 

Could we build a motion tracing camera using wireless communication signals as the light source? This paper shows we can, we present the design and implementation ofWiDeo, a novel system that enables accurate, high resolution, device free human motion tracing in indoor environments using WiFi signals and compact WiFi radios. The insight behind WiDeo is to mine the backscatter reflections from the environment that WiFi transmissions naturally produce to trace where reflecting objects are located and how they are moving. We invent novel backscatter measurement techniques that work in spite of the low bandwidth and dynamic range of WiFi radios, new algorithms that separate out the moving backscatter from the clutter that static reflectors produce and then trace the original motion that produced the backscatter in spite of the fact that it could have undergone multiple reflections. We prototype WiDeo using off-the-shelf software radios and show that it accurately traces motion even when there are multiple independent human motions occurring concurrently (up to 5) with a median error in the traced path of less than 7cm.

Kiran Joshi, Stanford University

Dinesh Bharadia, Stanford University

Manikanta Kotaru, Stanford University

Sachin Katti, Stanford University

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