Abstract
When people look at a face, they always build an affective subconscious impression of the person which is very useful information in social contact. Exploring relationship between facial appearance in portraits and personality impression is an interesting and challenging issue in multimedia area. In this paper, a novel method which can build relationship between facial appearance and personality impression is proposed. Low-level visual features are extracted on the defined face regions designed from psychology at first. Then, to alleviate the semantic gap between the low-level features and high-level affective features, mid-level feature set are built through clustering method. Finally, classification model is trained using our dataset. Comprehensive experiments demonstrate the effectiveness of our method by improving 26.24 % in F1-measure and 54.28 % in recall under similar precision comparing to state-of-the-art works. Evaluation of different mid-level feature combinations further illustrates the promising of the proposed method.
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Acknowledgments
This work is supported by the National Nature Science Foundation of China (No. 61402428, No. 61202208); the Fundamental Research Funds for the Central Universities (No. 201413021, No. 201513016).
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Yan, Y., Nie, J., Huang, L., Li, Z., Cao, Q., Wei, Z. (2016). Exploring Relationship Between Face and Trustworthy Impression Using Mid-level Facial Features. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9516. Springer, Cham. https://doi.org/10.1007/978-3-319-27671-7_45
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DOI: https://doi.org/10.1007/978-3-319-27671-7_45
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