Abstract
Descriptions of three methods for reconstructing incomplete facial expressions using principal component analysis are given, projection to the model plane, single component projection and replacement by the conditional mean – the facial expressions being represented by feature points. It is established that one method gives better reconstruction accuracy than the others. This method is used on a systematic reconstruction problem, the reconstruction of occluded top and bottom halves of faces. The results indicate that occluded-top expressions can be reconstructed with little loss of expression recognition – occluded-bottom expressions are reconstructed less accurately but still give comparable performance to human rates of facial expression recognition.
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Towner, H., Slater, M. (2007). Reconstruction and Recognition of Occluded Facial Expressions Using PCA. In: Paiva, A.C.R., Prada, R., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2007. Lecture Notes in Computer Science, vol 4738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74889-2_4
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DOI: https://doi.org/10.1007/978-3-540-74889-2_4
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