Combining SVM and CHMM classifiers for porno video recognition  被引量:2

Combining SVM and CHMM classifiers for porno video recognition

在线阅读下载全文

作  者:ZHAO Zhi-cheng 

机构地区:[1]School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China [2]Beijing Key Laboratory of Network System and Network Culture, Beijing University of Posts and Telecommunications, Beijing 100876, China

出  处:《The Journal of China Universities of Posts and Telecommunications》2012年第3期100-106,共7页中国邮电高校学报(英文版)

基  金:supported by the National Natural Science Foundation of China (90920001, 61101212);the Fundamental Research Funds for the Central Universities

摘  要:Pomo video recognition is important for Intemet content monitoring. In this paper, a novel pomo video recognition method by fusing the audio and video cues is proposed. Firstly, global color and texture features and local scale-invariant feature transform (SIFT) are extracted to train multiple support vector machine (SVM) classifiers for different erotic categories of image frames. And then, two continuous density hidden Markov models (CHMM) are built to recognize porno sounds. Finally, a fusion method based on Bayes rule is employed to combine the classification results by video and audio cues. The experimental results show that our model is better than six state-of-the-art methods.Pomo video recognition is important for Intemet content monitoring. In this paper, a novel pomo video recognition method by fusing the audio and video cues is proposed. Firstly, global color and texture features and local scale-invariant feature transform (SIFT) are extracted to train multiple support vector machine (SVM) classifiers for different erotic categories of image frames. And then, two continuous density hidden Markov models (CHMM) are built to recognize porno sounds. Finally, a fusion method based on Bayes rule is employed to combine the classification results by video and audio cues. The experimental results show that our model is better than six state-of-the-art methods.

关 键 词:pomo video recognition SVM keyframe CHMM AUDIO 

分 类 号:TP391.41[自动化与计算机技术—计算机应用技术] TS612.1[自动化与计算机技术—计算机科学与技术]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象