The Impact of Expertise on Brain Computer Interface Based Salient Image Retrieval

Autonomous decision making modules in computer vision application allow recognition and classification of different objects, persons, and events in images and video sequences and also make it possible to classify different sensor readings (e.g. images) according to their scientific saliencies. In this paper, we propose a new approach to create the training set for these algorithms by retrieving salient images using electroencephalogram (EEG) and brain computer interface (BCI) and rapid image presentation. To this end, two groups of subjects, namely, expert and novice subjects were asked to participate in our experiments. We show that a relatively high retrieval accuracy can be achieved for most of the subjects. Furthermore, to assess the impact of expertise on the retrieval process, we study their EEG signals separately and show that there is a clear difference in their brainwaves while observing salient images.

Published in:
Proceedings of 32nd Annual International Conference of the IEEE EMBS, 1646-1649
Presented at:
32nd Annual International Conference of the IEEE EMBS, Buenos Aires, Argentina, August 31- September 4, 2010
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 Record created 2010-09-23, last modified 2020-07-30

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