Mood Detection through Aesthetic Assessment of Videos using Deep Learning

  • Madhura Phatak
  • Shruti Asarkar

Abstract

role. Monitoring and predicting various
human’s feelings (happy, sad, anger, fear, etc.) is a challenging
task. Human interaction and carrier of feelings amongst
humans are accomplished mainly through five senses: touch,
smell, taste audio, visual. Considering Visual sense, images and
videos are important gradients in day-to-day life. It can
elevate/ depress the mood of a person. Digital contents of
multimedia are image, audio, video, text, and so on. The usage
of internet is tremendously increasing, so Internet bandwidth
and storage space, video data has been generated, published,
and spread robustly, and becoming an important of today’s big
data. This has encouraged the development of advanced
techniques for a wide scope of video understanding
applications including online advertising, Cinematography,
video retrieval, video surveillance, video data on Social sites,
etc. However, it is easy to convey a story to a viewer of video,
since a video is worth of thousands worth. And this story
actually creates a mood. This work is to detect the mood of
aesthetically pleasing videos that reflect on a person’s mood.

Keywords: Video aesthetics, Deep Learning, DCNN

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How to Cite
Phatak, M., & Asarkar, S. (2019). Mood Detection through Aesthetic Assessment of Videos using Deep Learning. Asian Journal For Convergence In Technology (AJCT). Retrieved from http://www.asianssr.org/index.php/ajct/article/view/741
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