Community Research and Development Information Service - CORDIS


IARTIST Report Summary

Project ID: 611362
Funded under: FP7-PEOPLE
Country: United Kingdom

Periodic Report Summary 1 - IARTIST (industry-Academia Research on Three-dimensional Image Sensing for Transportation)

iARTIST is an Industry-Academia Partnerships and Pathways project funded under the Marie Curie Action. It provides secondments to industrial engineers and university scientists to work in one another’s environment. The research within project started in February 2014, however, secondments starting in 2015. With additional staff members placed in the execution of the technical task of the project, we have achieved a number of technical results, including

a) A new pixel design for wide dynamic range imaging
CMOS pixels have typically linear response with limited dynamic range of 2-3 decades. This is disastrous for transportation applications as there is often bright light from vehicles as well as sun-glare. A new technique for achieving high dynamic range using matrix filling and compressive sensing, has been developed and is currently being considered for intellectual protection.

b) First stereoscopic imaging prototype for transportation
Monocular cameras are the mainstay of intelligent transportation systems. However, they do not provide depth information, which limits their ability to classify objects and perform measurements of sizes and distances. A new imaging system has been developed, by using a binocular system with off-the-shelf components, which has shown promising initial results. While the system performs admirably in lab, it requires large distances between cameras for real world applications to meet the international standards (OIML R91).

c) CNN based classification system for ITS
Utilising research on convoluted neural networks for feature extraction, the partnership has developed a new system to extract vehicles and people on road. This has been verified on traffic sequences recorded by VLA and early results are very promising

d) ITS Backbone
We have identified a new error limit for camera calibration using multi-sensory approach. We have already designed the early stages of ITS backbone including Software to identify logo and colours of vehicles in traffic scenes. This has been verified using typical traffic scenes. In addition, we have developed two sampling systems to reduce the data produced by cameras.

e) A threshold comparing pixel circuit for high dynamic range imaging
Intelligent transport systems require high dynamic range images. Even when these images are captured, it is difficult to reproduce them on a screen. This requires a complex operation, known as tone mapping, to be applied on each pixel’s response. We have developed a new pixel technology, which can produce real time tone mapped images at the focal plane itself.

Some of these developments have been unexpected and hence, we are considering intellectual protection. This may lead to some delays in publication; however, with industrial focus of this project, we expect that these to find an industrial application at a faster pace.

The project website is at


Stephen Conway, (Associate Director)
Tel.: +44 1865 289800
Fax: +44 1865 289801


Life Sciences
Record Number: 195380 / Last updated on: 2017-03-13