Video Content Detection Method Based on Audio-visual Features
Qun Cai, LU Song-nian, Yang Shu-tang · Jisuanji gongcheng · 2007
A novel audio-visual feature-based framework for porn video segment detection is presented,which extracts and analyses audio and video features independently,and combines their results to give out a final detection result.A support vector machine(SVM) is used to learn and then classify the audio sections,and skin info is used to give out a visual analysis result.Experiment results indicate that this approach has a high recognition rate,so it can be adopted to surveillance for video streams and segmentation of particular content in videos.