Improving Event detection in Cricket Videos Using Audio Feature Analysis

Abstract

This paper discusses an event detection approach based on audio, which proves to be effective when applied to the audio component of cricket television broadcaster’s video. In this approach, both crowed noise levels which is in the background and commentator voice which is in focus are considered correlated to key events in the time frame. Classifiers related to Hidden Markov Model (or HMM) are utilized as it is an efficient tool for modeling processes varying with time and broadly used in the area of speech recognition. This experiment done using cricket television broadcaster videos, was successful thus this method can be used for automatic indexing of audio (or video containing audio) for quick searching or segmentation.