Audio Feature Extraction and Analysis for Scene Segmentation and Classification
Journal of VLSI Signal Processing Systems - special issue on multimedia signal processing
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Early versus late fusion in semantic video analysis
Proceedings of the 13th annual ACM international conference on Multimedia
Early versus late fusion in semantic video analysis
Proceedings of the 13th annual ACM international conference on Multimedia
Creating audio keywords for event detection in soccer video
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Towards optimal audio "keywords" detection for audio content analysis and discovery
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Audio keywords generation for sports video analysis
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Classification of indecent videos by low complexity repetitive motion detection
AIPR '08 Proceedings of the 2008 37th IEEE Applied Imagery Pattern Recognition Workshop
Detecting pornographic video content by combining image features with motion information
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Semantic concept annotation based on audio PLSA model
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Pornprobe: an LDA-SVM based pornography detection system
MM '09 Proceedings of the 17th ACM international conference on Multimedia
A novel approach to musical genre classification using probabilistic latent semantic analysis model
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
A flexible framework for key audio effects detection and auditory context inference
IEEE Transactions on Audio, Speech, and Language Processing
A generic audio classification and segmentation approach for multimedia indexing and retrieval
IEEE Transactions on Audio, Speech, and Language Processing
Audio Keywords Discovery for Text-Like Audio Content Analysis and Retrieval
IEEE Transactions on Multimedia
The retrieval of motion event by associations of temporal frequent pattern growth
Future Generation Computer Systems
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Pornographic video detection based on multimodal fusion is an effective approach for filtering pornography. However, existing methods lack accurate representation of audio semantics and pay little attention to the characteristics of pornographic audios. In this paper, we propose a novel framework of fusing audio vocabulary with visual features for pornographic video detection. The novelty of our approach lies in three aspects: an audio semantics representation method based on an energy envelope unit (EEU) and bag-of-words (BoW), a periodicity-based audio segmentation algorithm, and a periodicity-based video decision algorithm. The first one, named the EEU+BoW representation method, is proposed to describe the audio semantics via an audio vocabulary. The audio vocabulary is constructed by k-means clustering of EEUs. The latter two aspects echo with each other to make full use of the periodicities in pornographic audios. Using the periodicity-based audio segmentation algorithm, audio streams are divided into EEU sequences. After these EEUs are classified, videos are judged to be pornographic or not by the periodicity-based video decision algorithm. Before fusion, two support vector machines are respectively applied for the audio-vocabulary-based and visual-features-based methods. To fuse their results, a keyframe is selected from each EEU in terms of the beginning and ending positions, and then an integrated weighted scheme and a periodicity-based video decision algorithm are adopted to yield final detection results. Experimental results show that our approach outperforms the traditional one which is only based on visual features, and achieves satisfactory performance. The true positive rate achieves 94.44% while the false positive rate is 9.76%.