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Automatic TV commercial block detection is a key component of an intelligent commercial management system. Rather than utilizing exclusively audio-visual characteristics like most previous works, We have proposed a SVM-DP scheme to collaboratively exploit audio-visual and global temporal characteristics associated with commercials. Firstly, likelihood values of commercial and general program are calculated...
Efficient and robust retrieval of commercial videos is an important topic for many applications such as commercial monitoring, market investigation. In this paper, we propose a two-step scheme to optimally incorporate the information of both visual and audio modalities into commercial retrieval. Firstly an efficient search method based on the extracted audio fingerprinting feature is proposed to yield...
Automatic scene detection is a fundamental step for efficient video searching and browsing. This paper presents our current work on scene detection that integrates three effective strategies into a single framework. For each video, firstly, a coherence signal is constructed by graph modal obtained from the similarity matrix in a temporal interval. Secondly, the signal is optimized by scene transition...
With the fast development of high-speed network and digital video recording technologies, broadcast video has been playing a more and more important role in our daily life. In this paper, we propose a novel news story segmentation scheme which can segment broadcast video into story units with multi-modal information fusion (MMIF) strategy. Compared with traditional methods, the proposed scheme extracts...
Avatars are virtual characters making the communication between user and machine more natural and interactive. The main advantage of using avatars within interfaces is to allow user to interact intuitively with the system by giving him the illusion of communicating with a real human. This illusion is obtained by mimicking human communication, i.e. giving avatar the ability of expressing emotions through...
Key frames play an important role in video abstraction. Clustering is a popular approach for key-frame extraction. In this paper, we propose a novel method for key-frame extraction based on dominant-set clustering. Compared with the existing clustering-based methods, the proposed method dynamically decides the number of key frames depending on the complexity of video shots, produces key frames in...
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