A Natural Language Driven Video Sequencer

Abstract

In this paper, we describe a natural language-based video editing system called video sequencer which can provide a real sequence of video images described by a script made of natural language sentences by searching a video image database. The database is indexed according to its semantic contents extracted from content annotation provided by directors. The sequencer is able to convert the queries formulated in natural language in the script for image retrieval queries. The video sequencer can increase the readability of the script for program production by using natural language processing. Moreover, the physical description of the video images, such as camera parameters, can be used in parallel with natural language sentences to constrain the search conditions. Thus more proper video sequences can be obtained.