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Active and dynamicinformation fusionfor facial expressionunderstanding fromimage sequences Yongmian ZhangQiang Ji2005 год

Active and dynamic information fusion for facial expression understanding from image sequences
статья из журнала

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Аннотация: This paper explores the use of multisensory information fusion technique with Dynamic Bayesian networks (DBNs) for modeling and understanding the temporal behaviors of facial expressions in image sequences. Our facial feature detection and tracking based on active IR illumination provides reliable visual information under variable lighting and head motion. Our approach to facial expression recognition lies in the proposed dynamic and probabilistic framework based on combining DBNs with Ekman's Facial Action Coding System (FACS) for systematically modeling the dynamic and stochastic behaviors of spontaneous facial expressions. The framework not only provides a coherent and unified hierarchical probabilistic framework to represent spatial and temporal information related to facial expressions, but also allows us to actively select the most informative visual cues from the available information sources to minimize the ambiguity in recognition. The recognition of facial expressions is accomplished by fusing not only from the current visual observations, but also from the previous visual evidences. Consequently, the recognition becomes more robust and accurate through explicitly modeling temporal behavior of facial expression. In this paper, we present the theoretical foundation underlying the proposed probabilistic and dynamic framework for facial expression modeling and understanding. Experimental results demonstrate that our approach can accurately and robustly recognize spontaneous facial expressions from an image sequence under different conditions.
Год издания: 2005
Авторы: Yongmian Zhang, Qiang Ji
Издательство: IEEE Computer Society
Источник: IEEE Transactions on Pattern Analysis and Machine Intelligence
Ключевые слова: Face and Expression Recognition, Emotion and Mood Recognition, Face recognition and analysis
Другие ссылки: IEEE Transactions on Pattern Analysis and Machine Intelligence (HTML)
CiteSeer X (The Pennsylvania State University) (PDF)
CiteSeer X (The Pennsylvania State University) (HTML)
PubMed (HTML)