Learning to Rank Images from Eye Movements

Pasupa, Kitsuchart, Saunders, Craig, Szedmak, Sandor, Klami, Arto, Kaski, Samuel and Gunn, Steve (2009) Learning to Rank Images from Eye Movements. At Proceeding of 2009 IEEE 12th International Conference on Computer Vision (ICCV'2009) Workshop on Human-Computer Interaction (HCI'2009), Kyoto, Japan, 27 Sep - 04 Oct 2009. IEEE, 2009-2016.


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Combining multiple information sources can improve the accuracy of search in information retrieval. This paper presents a new image search strategy which combines image features together with implicit feedback from users' eye movements, using them to rank images. In order to better deal with larger data sets, we present a perceptron formulation of the Ranking Support Vector Machine algorithm. We present initial results on inferring the rank of images presented in a page based on simple image features and implicit feedback of users. The results show that the perceptron algorithm improves the results, and that fusing eye movements and image histograms gives better rankings to images than either of these features alone.

Item Type: Conference or Workshop Item (Speech)
Additional Information: Event Dates: 27 September - 4 October 2009
Divisions : Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Electronic & Software Systems
ePrint ID: 267964
Accepted Date and Publication Date:
4 October 2009Published
Date Deposited: 27 Sep 2009 14:54
Last Modified: 31 Mar 2016 14:15
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/267964

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