Automatic segmentation of news items in a MPEG-2 stream is a significant research topic for implementing an antomatic cataloging system of news video. This paper presents an approach which employes audio and video fea...Automatic segmentation of news items in a MPEG-2 stream is a significant research topic for implementing an antomatic cataloging system of news video. This paper presents an approach which employes audio and video feature information to automatically segment news items. Combining the analysis techniques of audio and video can overcome the weakness of the approach which only uses the image analysis techniques. This combination makes our appoach more widely adaptable to variable existence situations of news items. The proposed approach detects silence clips in accompanying audio,and integrates with shot segmentation results ,as well as anchor shot detection results ,to determine boundaries between two news items. Experimental results show that the integration of audio and video features is an effective approach to solve the problem of automatic news items segmentation.展开更多
Detecting anchor shots accurately is very improtant for automatically parsing news video and extracting meaningful news items. The paper proposes a fast anchor shot detection algorithm,which is based on backgroud chor...Detecting anchor shots accurately is very improtant for automatically parsing news video and extracting meaningful news items. The paper proposes a fast anchor shot detection algorithm,which is based on backgroud choronminance and skin tone models. The attractive characteristics of the algorithminclude only simple computation involved. At the same time,it operates in MPEG compression domain,which makes the detection speed very fast. The algorithm was evaluated on a big test set containing more than 480000 frames and news video from two different TV stations. More than 98% accuracy and 100% recall have been gained. The experiment results also show the system has an average detection speed of 77.55 f/s. The experiments demonstrate the algorithm is a fast and effective one.展开更多
文摘Automatic segmentation of news items in a MPEG-2 stream is a significant research topic for implementing an antomatic cataloging system of news video. This paper presents an approach which employes audio and video feature information to automatically segment news items. Combining the analysis techniques of audio and video can overcome the weakness of the approach which only uses the image analysis techniques. This combination makes our appoach more widely adaptable to variable existence situations of news items. The proposed approach detects silence clips in accompanying audio,and integrates with shot segmentation results ,as well as anchor shot detection results ,to determine boundaries between two news items. Experimental results show that the integration of audio and video features is an effective approach to solve the problem of automatic news items segmentation.
文摘Detecting anchor shots accurately is very improtant for automatically parsing news video and extracting meaningful news items. The paper proposes a fast anchor shot detection algorithm,which is based on backgroud choronminance and skin tone models. The attractive characteristics of the algorithminclude only simple computation involved. At the same time,it operates in MPEG compression domain,which makes the detection speed very fast. The algorithm was evaluated on a big test set containing more than 480000 frames and news video from two different TV stations. More than 98% accuracy and 100% recall have been gained. The experiment results also show the system has an average detection speed of 77.55 f/s. The experiments demonstrate the algorithm is a fast and effective one.
