SUPPORT VECTOR MACHINE BASED APPROACH FOR TRANSLATING VIDEO SCENERIES TO NATURAL LANGUAGE DESCRIPTIONS

Abstract

Human uses communication language either by written, spoken or typed to describe visual the world around them. So, the study of text description for any video goes increasing. This paper represents a framework that gives output as a description for any video having a maximum size of 50 seconds by using natural language processing. The framework is divided into two sections called training and testing. The training section is used to train the video with its description like activities of objects present in that video. The trained data is stored into the database with its features of scenario of video. Another section is testing section. The testing section is used to test the video and retrieve the output as description of video. By using Natural language processing sentences are generated from objects and their activities present in the video.