Abstract:
"
Since the innovation of the microprocessor and the computer, researchers have been
pushing the limits to make it similar to a human, currently a computer can speak,
think, hear and even see but the only piece which is missing from the puzzle is
emotions, and day by day we are getting closer to this reality as well, the study of
emotion-based computing is termed affective computing.
Video production and marketing is one of the most demanding fields and the
moment, and there is a high demand for content which are emotionally rich,
however there are very few products which caters to this need of emotional based
video marketing.
There are multiple methods in detecting emotions such as facial expression-based
emotion recognition, physiological signals-based emotion recognition, speech based emotion recognition and text-based emotion recognition. Through this
research the author tries a hybrid approach using facial expressions and
physiological signals such as heart rate and galvanic skin responses inputs to predict
the user’s emotion while a user is watching a video and also analyzing the video
which is being watched for the emotions expressed by the characters in it and
provide useful analytics for video creators so that they can produce more
emotionally appealing videos."
