A Review on Key Features and Novel Methods for Video Summarization

Abstract

In this paper, we discuss techniques, algorithms, evaluation methods used in online, offline, supervised, unsupervised, multi-video and clustering methods used for Video Summarization/Multi-view Video Summarization from various references. We have studied different techniques in the literature and described the features used for generating video summaries with evaluation methods, supervised, unsupervised, algorithms and the datasets used. We have covered the survey towards the new frontier of research in computational intelligence technique like ANN (Artificial Neural Network) and other evolutionary algorithms for VS using both supervised and unsupervised methods. We highlight on single, multi-video summarization with features like video, audio, and semantic embeddings considered for VS in the literature. A careful presentation is attempted to bring the performance comparison with Precision, Recall, F-Score, and manual methods to evaluate the VS.