| Abstract: | Emotional space refers to
a multi-dimensional emotional model that describes a group of subjective
feelings or emotions. Since the
existing discrete emotional space is mainly aimed at human’s primary emotions, it cannot describe the complex
emotions evoked when watching movies. In order to solve this problem, an
emotional fusion space for videos was
constructed by selecting movies and TV dramas with rich emotional semantics as
the research objects. Firstly,
emotional words based on movie and TV drama videos are acquired and analyzed by
using subjective evaluation and
semantic analysis methods. Then, the emotional word vectors obtained from the
above analysis are fused,
reduced dimension by t-distributed stochastic neighbor embedding (t-SNE)
algorithm, and clustered by bisecting K-means
clustering algorithm to get a discrete emotional space for movie and TV drama videos. This emotional
fusion space can obtain different categories by changing the value of the
emotion classification number without
re-labeling and calculation. |
