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Hammal, Z., & Massot, C. (2010). Holistic and feature-based information towards dynamic multi-expressions recognition. In Z. Hammal, & C. Massot (Ed.), VISAPP 2010. International Conference on Computer Vision Theory and Applications.
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 Holistic and feature-based processings are both shown to be involved differently in the analysis of facial expression by human observer. The current paper proposes a novel method based on the combination of both approaches for the segmentation of “emotional segments” and the dynamic recognition of the corresponding facial expressions. The proposed model is a new advancement of a previously proposed feature-based model for static facial expression recognition (Hammal et al., Approximate Reasoning, 2007). First, a new spatial filtering method is introduced for the holistic processing of the face towards the automatic segmentation of “emotional segments”. Secondly, the new filtering-based method is applied as a feature-based processing for the automatic and precise segmentation of the transient facial features and estimation of their orientation. Third, a dynamic and progressive fusion process of the permanent (such as eyes, eyebrows and mouth) and transient facial feature deformations is made inside each “emotional segment” for a temporal recognition of the corresponding facial expression. Experimental results show the robustness of the holistic and feature-based analysis, notably for the analysis of multi-expression sequences. Moreover compared to the static facial expression classification, the obtained performances increase by 12 % and compare favorably to human observers’ performances
 
 
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