Summarization of videos by analyzing affective state of the user through crowdsource |
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| Affiliation: | 1. Department of Computer Science Engineering, Indian Institute of Technology, Roorkee, India;2. Department of Electrical Science, Indian Institute of Technology, Bhubaneswar, India;3. Department of IT Engineering, Sookmyung Women’s University, Republic of Korea;1. Department of Computer Science and Engineering, MNM Jain Engineering College, Chennai, Tamil Nadu, India;2. Department of Information Technology, Adhiyamaan College of Engineering, Hosur, Tamil Nadu, India;1. The Center for Chinese Modern City Studies, East China Normal University, China;2. School of Urban and Regional Science, East China Normal University, China;1. CIML Group, Institute of Biophysics, University of Regensburg, 93040 Regensburg, Germany;2. Institute of Information Science, University of Regensburg, Germany;3. IEETA, DETI, Universidade de Aveiro, 3810-193 Aveiro, Portugal;4. Institute of Experimental Psychology, University of Regensburg, Germany;5. Clinic of Neurosurgery, University Hospital Regensburg, Germany;1. Biomedical, IMage and Signals (BIMS) Research Group, Department of Electrical & Electronic Engineering, United International University, Dhaka, Bangladesh;2. Institute for Sustainable Industries & Liveable Cities, Victoria University, Melbourne, Australia;3. Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba, Australia;4. Cyberspace Institute of Advanced Technology (CIAT), Guangzhou University, Guangzhou, China;1. Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran;2. Rayan Center for Neuroscience and Behavior, Ferdowsi University of Mashhad, Mashhad, Iran;3. Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran |
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| Abstract: | Video summarization is one of the key techniques to access and manage a huge chunk of videos. Video summarization is used to extract the effective contents of a video sequence to generate a concise representation of its content. The involvement of crowdsourcing models in recent years is effectively used by researchers in E-commerce domain to increase the quality of the data contents. In this paper, we present a video summarization framework based on users emotion while they watch videos by analyzing cerebral activities through Electroencephalogram (EEG) signals. Three emotions, namely happy, sad and neutral have been extracted from the EEG signals. Video frames have been synchronized with EEG signals and tagged with various emotions. Finally, a crowdsourcing model has been used for effective summarization of the videos. The qualitative assessment of video summarization has been conducted with the help of user ratings using online Google Forms application. EEG signals of 28 users have been recorded while video streams of different emotions. An average accuracy of 83.93% has been recorded in emotion classification using crowdsourcing. Output summarized videos include dynamic video skims and the corresponding audio stream for better understanding. |
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| Keywords: | Video summarization Electroencephalogram (EEG) Crowdsourcing Random Forest |
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