Recognition of Different Modes of Human Thinking during Processing Visual Images of Histograms and Scenes

Abstract:

To investigate the different modes of human thinking, we designed an eye tracking experiment during people recognized two category images of histograms and scenes, and used the support vector machine (SVM) classification algorithm to classify these eye movement data. The results of statistical analysis showed that there were significant differences in saccade distance and pupil diameter between these two category images. By the feature selection, normalization of data preprocessing, and SVM classification, the results of classification analysis showed that there was a better performance on the classification of the histograms and scenes. These results suggest we can identify the modes of human thinking through the SVM classification methods based on the eye movement data.

• Periodical: Applied Mechanics and Materials (Volumes 333-335)
• Pages: 1328-1331
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.333-335.1328
• Online since: July 2013
• Authors: Mi Li, Sheng Fu Lu, Xue Tan, Yu Zhou, Ning Zhong
• Keywords: Eye Movement, Histograms, Modes of Human Thinking, Scenes, Support Vector Machine (SVM)

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