A Deep Learning Framework for Monitoring Audience Engagement in Online Video Events
Alexandros Vrochidis,
Nikolaos Dimitriou,
Stelios Krinidis
et al.
Abstract:This paper introduces a deep learning methodology for analyzing audience engagement in online video events. The proposed deep learning framework consists of six layers and starts with keyframe extraction from the video stream and the participants’ face detection. Subsequently, the head pose and emotion per participant are estimated using the HopeNet and JAA-Net deep architectures. Complementary to video analysis, the audio signal is also processed using a neural network that follows the DenseNet-121 architectu… Show more
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