- Title
- Scene perception using pareidolia of faces and expressions of emotion
- Creator
- Hong, Kenny; Chalup, Stephan K.; King, Robert A.; Ostwald, Michael J.
- Relation
- 2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC). Proceedings of 2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC) (Singapore 16-19 April, 2013) p. 79-86
- Publisher Link
- http://dx.doi.org/10.1109/CICAC.2013.6595224
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2013
- Description
- The aim of this study is to simulate the pareidolia capability of humans to produce an emotional response to a scene using analysis of facial expressions associated with abstract face-like patterns. We developed a system that uses a holistic face detector and a facial expression classifier. The υ and SVDD One-Class Support Vector Machines (SVM) were evaluated for creating a holistic face detector, which looks for faces that can vary from natural faces to minimal face-like patterns. A Pairwise Adaptive C and υ-SVM (pa-SVM) were evaluated for creating the facial expression classifier. In both scenarios, a dataset of human faces and facial expressions was used to produce a number of preprocessed images (grayscale, histogram equalised grayscale; and their respective Sobel and Canny edges) at a number of resolutions for analysis. A Gaussian and a degree two polynomial kernel were used with the SVM methods and the results were obtained using a 10 fold cross validation technique. A concern with the face detectors is verifying that they can look for minimal face-like patterns empirically. To address this concern, we created cartoon faces of the human face dataset and degraded these cartoon faces to produce an array of minimal face-like patterns. We then evaluated the face detectors and facial expression classifiers with the best model parameters on these cartoon faces. The outcome is a holistic system with the potential to describe a scene by producing an array of emotion scores corresponding to Ekman's seven Universal Facial Expressions of Emotion.
- Subject
- υ-SVM; Canny edge; facial expression classifier; facial expressions; histogram equalised grayscale image; holistic face detector; human pareidolia capability; pa-SVM; pairwise adaptive C SVM; preprocessed images; scene perception; Gaussian kernel; SVDD one-class support vector machines; Sobel edge; abstract face-like patterns; cartoon faces; cross validation technique; degree two polynomial kernel; face pareidolia
- Identifier
- http://hdl.handle.net/1959.13/1042958
- Identifier
- uon:14151
- Language
- eng
- Full Text
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