Saman Riaz1, Ali Arshad2, Shahab S. Band3,*, Amir Mosavi4
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2301-2312, 2023, DOI:10.32604/cmc.2023.028333
Abstract Personality distinguishes individuals’ patterns of feeling, thinking, and behaving. Predicting personality from small video series is an exciting research area in computer vision. The majority of the existing research concludes preliminary results to get immense knowledge from visual and Audio (sound) modality. To overcome the deficiency, we proposed the Deep Bimodal Fusion (DBF) approach to predict five traits of personality-agreeableness, extraversion, openness, conscientiousness and neuroticism. In the proposed framework, regarding visual modality, the modified convolution neural networks (CNN), more specifically Descriptor Aggregator Model (DAN) are used to attain significant visual modality. The proposed model extracts audio representations for greater efficiency… More >
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