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RapID: A Framework for Fabricating Low-Latency Interactive Objects with RFID Tags

RapID: A Framework for Fabricating Low-Latency Interactive Objects with RFID Tags

by Sarah Frigg | May 7, 2016 | Digital Fabrication, Uncategorized, Visual Computing

RapID: A Framework for Fabricating Low-Latency Interactive Objects with RFID Tags   In this work, we show how to achieve low-latency manipulation and movement sensing with off-the-shelf RFID tags and readers. May 7, 2016CHI Interactivity 2016   Authors Andrew...
PaperID: A Technique for Drawing Functional Battery-Free Wireless Interfaces on Paper

PaperID: A Technique for Drawing Functional Battery-Free Wireless Interfaces on Paper

by Sarah Frigg | May 7, 2016 | Uncategorized

PaperID: A Technique for Drawing Functional Battery-Free Wireless Interfaces on Paper   We describe techniques that allow inexpensive, ultra-thin, battery-free Radio Frequency Identification RFID tags to be turned into simple paper input devices. May 7, 2016CHI...
High-Q and Over-Coupled Tuning for Near-Field RFID Systems

High-Q and Over-Coupled Tuning for Near-Field RFID Systems

by Sarah Frigg | May 3, 2016 | Uncategorized

High-Q and Over-Coupled Tuning for Near-Field RFID Systems   This work will show both theoretically and through experimentation that using high Q coils in the over-coupled regime supports extension of read range in near field RFID systems by 81% or more compared to...
An Energy-interference-free Hardware-Software Debugger for Intermittent Energy-harvesting Systems

An Energy-interference-free Hardware-Software Debugger for Intermittent Energy-harvesting Systems

by Sarah Frigg | Apr 2, 2016 | Wireless Communication and Ubiquitous Computing

An Energy-interference-free Hardware-Software Debugger for Intermittent Energy-harvesting Systems   We propose the Energy-interference-free Debugger, a hardware and software platform for energy-interference-free monitoring and debugging of intermittent systems. April...
Predicting Movie Ratings from Audience Behaviors

Predicting Movie Ratings from Audience Behaviors

by Martina Megaro | Mar 24, 2016 | Machine Learning

Predicting Movie Ratings from Audience Behaviors We propose a method of representing audience behavior through facial and body motions from a single video stream, and use these features to predict the rating for feature-length movies. March 24, 2016 IEEE Winter...
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