2010
DOI: 10.1007/978-3-642-11628-5_36
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Abstract: Abstract. Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always tar… Show more

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Cited by 1 publication
(3 citation statements)
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“…For detecting features, still many of the current approaches do not automatically extract the features, do not consider time sequence frames, and it is common to divide the image in parts instead of analyzing the whole face image at once. A step forward was done in [18] and [13,10] were the features were detected automatically. About the classification techniques, we found on literature: template-based classification [25], fuzzy classification, ANN based classification [12], HMM based classification and also Bayesian classification [3] [17] and [18].…”
Section: Proposed Approaches To Automatic Emotionmentioning
confidence: 99%
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“…For detecting features, still many of the current approaches do not automatically extract the features, do not consider time sequence frames, and it is common to divide the image in parts instead of analyzing the whole face image at once. A step forward was done in [18] and [13,10] were the features were detected automatically. About the classification techniques, we found on literature: template-based classification [25], fuzzy classification, ANN based classification [12], HMM based classification and also Bayesian classification [3] [17] and [18].…”
Section: Proposed Approaches To Automatic Emotionmentioning
confidence: 99%
“…Most state-of-the-art in the area of emotive robots do not run in real-time, being then still inapplicable to real cases of human-robot-interaction applications. However recent researches like [20] and [15] shows result about two Bayesian classifiers inside a structure for human-robot-interaction that are applicable to HRI in real-time. These classifiers have both the purpose to classify human emotional state among the scope {anger,fear,sad,neutral and happy}.…”
Section: Emotive Robotsmentioning
confidence: 99%
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