The paper presents a model of visual attention combined with eye tracking to drive content-based retrieval of image data in order to facilitate understanding and development of new adaptive eye guided representation of image sequences. The bottom-up component of the proposed visual attention model is based on the extended Itti-Koch saliency model incorporating conjunction search and temporal aspects of sequences of natural images. The top-down component is a gaze-prediction model designed to associate measured eye tracking locations and features extracted from images. This approach permits the detection and separation of attention-driven regions of interest and their processing with the highest accuracy, while the remaining part of the image (the background) is reproduced with lower quality.
Mariofanna G. Milanova, Stuart Harvey Rubin, Roume