Although clever – attaining the best accuracy of 72.31%, this idea couldn’t work for all applications, and indeed it did not win the second challenge where only the raw eye movement data was given. In this more difficult problem, Tuomas Lepola of the University of Helsinki was most successful, with an accuracy of 64.8% on unseen test data. The future looks promising for this remarkable area of research. Since the competitions were run, PASCAL funded a “pump-priming” project to investigate the ideas further. In this recent feasibility study, researchers from the Helsinki University of Technology, the University of Southampton and UCL collaborated to try an even harder task: could a computer learn whether you found a whole section of text relevant to a single keyword or search topic? Would the pattern of words scanned by your eyes provide enough clues for the computer to figure out what you are looking for? David R. Hardoon and John Shawe-Taylor were responsible for the creation of the machine learning software that had to perform this task.

Eye Tools The idea of eye tracking is now big business. Eyetools is a company specialising in the area, providing their own analysis of eye movements when presented with adverts and web pages of a huge range of commercial and corporate clients. Rather than helping users to find relevant content, Eyetools helps their corporate clients to design eye catching websites by analysing where people look. If nobody ever looks at an advert, headline or contents list, then this is indicative of a serious design flaw. In this way Eyetools is able to help companies produce the most effective visual designs possible. Companies such as Eyetools work offline, analysing data in order to improve a document. Researchers of PINView want to use machine learning and analyse our gazes in real time.