IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
PicSOM—content-based image retrieval with self-organizing maps
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Kernel methods for predicting protein--protein interactions
Bioinformatics
Perceptual image retrieval using eye movements
International Journal of Computer Mathematics - Computer Vision and Pattern Recognition
Can relevance of images be inferred from eye movements?
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Can eyes reveal interest? Implicit queries from gaze patterns
User Modeling and User-Adapted Interaction
Passive Eye Monitoring: Algorithms, Applications and Experiments
Passive Eye Monitoring: Algorithms, Applications and Experiments
Finding the user's interest level from their eyes
Proceedings of the 2010 ACM workshop on Social, adaptive and personalized multimedia interaction and access
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
An eye-tracking-based approach to facilitate interactive video search
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Gaze movement inference for user adapted image annotation and retrieval
SBNMA '11 Proceedings of the 2011 ACM workshop on Social and behavioural networked media access
Biometric identification based on the eye movements and graph matching techniques
Pattern Recognition Letters
Making use of eye tracking information in image collection creation and region annotation
Proceedings of the 20th ACM international conference on Multimedia
Human behavior sensing for tag relevance assessment
Proceedings of the 21st ACM international conference on Multimedia
Can a clipboard improve user interaction and user experience in web-based image search?
HCI International'13 Proceedings of the 15th international conference on Human Interface and the Management of Information: information and interaction design - Volume Part I
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In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. These rankings are learned in order to present a user with a new set of images that are relevant to their task. Requiring such explicit information may not be feasible in a number of cases, we consider the setting where the user provides implicit feedback, eye movements, to assist when performing such a task. This paper explores the idea of implicitly incorporating eye movement features in an image ranking task where only images are available during testing. Previous work had demonstrated that combining eye movement and image features improved on the retrieval accuracy when compared to using each of the sources independently. Despite these encouraging results the proposed approach is unrealistic as no eye movements will be presented a-priori for new images (i.e. only after the ranked images are presented would one be able to measure a user's eye movements on them). We propose a novel search methodology which combines image features together with implicit feedback from users' eye movements in a tensor ranking Support Vector Machine and show that it is possible to extract the individual source-specific weight vectors. Furthermore, we demonstrate that the decomposed image weight vector is able to construct a new image-based semantic space that outperforms the retrieval accuracy than when solely using the image-features.