Abstract: Although cameras are an information rich sensing modality,
their use in sensor networks is very often prohibited by factors such as
power, computation cost, storage, communication and privacy. In this
talk I will present information selective and privacy preserving address
event imagers for sensor networks. I report on two generations of CMOS
image sensors with digital output.
The imagers embed an ALOHA MAC interface for unfettered self-timed pixel
read-out targeted to energy-aware sensor network applications. The image
sensors present very high dynamic range and ultra-low power operation.
This characteristics allow the sensor to operate in different lighting
conditions and for years on the sensor network node power budget.
Instead of providing full images with a high degree of redundancy, our
efforts in the design of these image sensors specialize on selecting a
handful of features from a scene and
outputting these features in address event representation. I present our
initial results in modeling and evaluating the address-event image
sensors. Using three different platforms that we have developed
we illustrate how to model address-event cameras, how address-event
representation can reduce processing and how these properties can be
exploited further inside the network.
Keywords: Image sensor, CMOS, sensor network, ALOHA, low-power imager,
address-event.