A genuine smile is indeed in the eyes – The computer aided non-invasive analysis of the exact weight distribution of human smiles across the face
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AbstractUnderstanding the detailed differences between posed and spontaneous smiles is an important topic with a range of applications such as in human-computer interaction, automatic facial emotion analysis and in awareness systems. During the past decade or so, there have been very promising solutions for accurate automatic recognition and detailed facial emotion analysis. To this end, many methods and techniques have been proposed for distinguishing between spontaneous and posed smiles. Our aim here is to go beyond the present state of the art in this field. Hence, in this work, we are concerned with understanding the exact distribution of a smile – both spontaneous and posed – across the face. To do this, we utilise a lightweight computational framework which we have developed to analyse the dynamics of human facial expressions. We utilise this framework to undertake a detailed study of the smile expression. Based on computing the optical flow across the face – especially across key parts of the face such as the mouth, the cheeks and around the eyes – we are able to accurately map the dynamic weight distribution of the smile expression. To validate our computational model, we utilise two publicly available datasets, namely the CK + dataset in which the subjects express posed smiles and the MUG dataset in which the subjects express genuine smiles. Our results not only confirm what already exists in the literature – i.e. that the spontaneous genuine smile is truly in the eyes – but it also gives further insight into the exact distribution of the smile across the face.
CitationUgail H and Al-dahoud A (2019) A genuine smile is indeed in the eyes - The computer aided non-invasive analysis of the exact weight distribution of human smiles across the face. Advanced Engineering Informatics. 42: 100967.
Link to publisher’s versionhttps://doi.org/10.1016/j.aei.2019.100967
Showing items related by title, author, creator and subject.
Distinguishing between genuine and posed smilesUgail, Hassan; Aldahoud, Ahmad A.A. (2019-04-18)This chapter presents an application of computational smile analysis framework discussed earlier. Here we discuss how one could utilise a computational algorithm to distinguish between genuine and posed smiles. We utilise aspects of the computational framework discussed in Chap. 2 to process and analyse the smile expression looking for clues to determine the genuineness of it. Equally, we discuss how the exact distribution of a smile across the face, especially the distinction in the weight distribution between a genuine and a posed smile can be achieved.
The biometric characteristics of a smileUgail, Hassan; Aldahoud, Ahmad (2019-04-18)Facial expressions have been studied looking for its diagnostic capabilities in mental health and clues for longevity, gender and other such personality traits. The use of facial expressions, especially the expression of smile, as a biometric has not been looked into great detail. However, research shows that a person can be identified from their behavioural traits including their emotional expressions. In this Chapter, we discuss a novel computational biometric model which can be derived from the smile expression. We discuss how the temporal components of a smile can be utilised to show that similarities in the smile exist for an individual and it can be enabled to create a tool which can be utilised as a biometric.
Computational Techniques for Human Smile AnalysisUgail, Hassan; Aldahoud, Ahmad A.A. (Springer, 2019-06)Explains how to implement computational techniques for human smile analysis Shares insights into the human personality traits hidden in a smile Enriches the understanding of human emotions through examples of face analysis Includes key examples of the practical use of computer based smile analysis.