مشاهده مشخصات مقاله
Hybrid Feature and Decision Level Fusion of Face and Speech Information for Bimodal Emotion Recognition
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Authors |
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Muharram Mansoorizadeh
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Nasrollah Moghaddam Charkari
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Conference |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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Abstract |
A hybrid feature and decision level information fusion
architecture is proposed for human emotion recognition
from facial expression and speech prosody. An active buffer
stores the most recent information extracted from face and
speech. This buffer allows fusion of asynchronous information
through keeping track of individual modality updates.
The contents of the buffer will be fused at feature level; if
their respective update times are close to each other. Based
on the classifiers’ reliability, a decision level fusion block
combines results of the unimodal speech and face based
systems and the feature level fusion based classifier. Experimental
results on a database of 12 people show that the
proposed fusion architecture performs better than unimodal
classification, pure feature level fusion and decision level
fusion. |
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قیمت |
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برای اعضای سایت : 100,000 Rial
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برای دانشجویان عضو انجمن : 20,000 Rial
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برای اعضای عادی انجمن : 40,000 Rial
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خرید مقاله
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