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Bi-modal first impressions recognition using temporally ordered deep audio and stochastic visual features
, Vismay Patel, Ashish Mishra, Arulkumar Subramaniam, Prashanth Balasubramanian
Published in Springer Verlag
2016
Volume: 9915 LNCS
   
Pages: 337 - 348
Abstract
We propose a novel approach for First Impressions Recognition in terms of the Big Five personality-traits from short videos. The Big Five personality traits is a model to describe human personality using five broad categories: Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness. We train two bi-modal end-to-end deep neural network architectures using temporally ordered audio and novel stochastic visual features from few frames, without over-fitting. We empirically show that the trained models perform exceptionally well, even after training from a small sub-portions of inputs. Our method is evaluated in ChaLearn LAP 2016 Apparent Personality Analysis (APA) competition using ChaLearn LAP APA2016 dataset and achieved excellent performance. © Springer International Publishing Switzerland 2016.
About the journal
JournalData powered by TypesetLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherData powered by TypesetSpringer Verlag
ISSN03029743
Open AccessYes
Concepts (14)
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    Computer vision
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    Deep learning
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    Deep neural networks
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    Network architecture
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    Neural networks
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    Stochastic systems
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    APPARENT PERSONALITY ANALYSIS
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    BIG FIVE
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    End to end
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    FIRST IMPRESSIONS
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    OVERFITTING
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    PERSONALITY TRAITS
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    VISUAL FEATURE
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    Modal analysis