Visual codes are used to embed digital data in physical objects, or they are shown in video sequences to transfer data over screen/camera links. Existing codes either carry limited data to make them robust against a range of channel conditions (e.g., low camera quality or long distances), or they support a high data capacity but only work over a narrow range of channel conditions. We present Focus, a new code design that does not require this explicit trade-off between code capacity and the reader’s channel quality. Instead,Focus builds on concepts from OFDM to encode data at different levels of spatial detail. This enables each reader to decode as much data from a code as its channel quality allows. We build a prototype of Focus devices and evaluate it experimentally. Our results show that Focus gracefully adapts to the reader’s channel, and that it provides a significant performance improvement over recently proposed designs, including Strata and PixNet.

We aim to to objectively characterise the service users experience from their home Internet connections. The attributes of an Internet connection (e.g., bandwidth and loss rate) dictate the service quality that can be achieved over it. American video use is increasing rapidly with 70% of broadband users under the age of 35 getting some of their TV from online sources. Measurement of such connections is crucial, their characterisation is useful not only for human users (so people know what service they can receive) but also for the users’ devices for adaptive behaviour. Furthermore, large-scale characterisation data of individual connections can be collated into a characterisation of the whole network. In this paper we will present a distributed measurement system that we have built and the choices that comprise its design.

Visual codes, such as QR codes, offer a low-cost alternative to RF technology when digital data needs to be embedded in objects in the physical world. However, in order to sup- port receivers with a poor visual channel, e.g. low-resolution cameras, most visual codes are designed for low data capacity and short reading distances. We present our work-in-progress on Focus, a visual code that avoids earlier work’s explicit trade-off between code capacity and channel quality. Rather than encoding the pay- load directly into individual pixels, Focus encodes the pay- load over a range of spatial frequencies. As a result, even a receiver with a very poor channel (e.g., with low-resolution camera or motion blur) can still partly decode a Focus code, because the code’s low-frequency components are robust to common channel impairments. A receiver with a good channel can decode all data from the same code. In our demo, we will present a prototype of Focus for smartphones and showcase how it deals with common impairments of the visual channel.