A Hybrid Fuzzy Approach for Human Eye Gaze Pattern Recognition

Abstract. Face perception and text reading are two of the most developed visual perceptual skills in humans. Understanding which features in the respective visual patterns make them differ from each other is very important for us to investigate the correlation between human's visual behavior and cognitive processes. We introduce our fuzzy signatures with Levenberg-Marquardt optimisation method based hybrid approach for recognising the different eye-gaze patterns when a human is viewing faces or text documents. Our experiment results show effectiveness of using this method for the real world case. A further comparison with Support Vector Machines (SVM) also demonstrates that by defining the classification process in the similar way to SVM, our hybrid approach is able to provide a comparable performance but with a more interpretable form of the learned structure. Key words: Eye-gaze Pattern, Fuzzy Signatures, WRAO, LevenbergMarquardt Optimisation, SVM.

• Type: Conference
• Year: 2008
• Where: ICONIP
• Authors: Dingyun Zhu, B. Sumudu U. Mendis, Tom Gedeon, Akshay Asthana, Roland Goecke
• Keywords: Eye-gaze Pattern, Fuzzy Signatures, Hybrid Approach, ICONIP 2008, Information Technology