The nature of statistical learning theory
The nature of statistical learning theory
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine learning in automated text categorization
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Retrieval of Commercials by Semantic Content: The Semiotic Perspective
Multimedia Tools and Applications
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Story Segmentation and Detection of Commercials in Broadcast News Video
ADL '98 Proceedings of the Advances in Digital Libraries Conference
Video Scene Segmentation via Continuous Video Coherence
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Time-Constrained Clustering for Segmentation of Video into Story Unites
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
On the detection and recognition of television commercials
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Fast and robust short video clip search using an index structure
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Live sports event detection based on broadcast video and web-casting text
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Scene Determination Based on Video and Audio Features
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
A probabilistic framework for semantic video indexing, filtering,and retrieval
IEEE Transactions on Multimedia
Event based indexing of broadcasted sports video by intermodalcollaboration
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Computable scenes and structures in films
IEEE Transactions on Multimedia
A quick search method for audio and video signals based on histogram pruning
IEEE Transactions on Multimedia
A unified framework for semantic shot classification in sports video
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Automated high-level movie segmentation for advanced video-retrieval systems
IEEE Transactions on Circuits and Systems for Video Technology
TV broadcast macro-segmentation: metadata-based vs. content-based approaches
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TV ad video categorization with probabilistic latent concept learning
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Scene duplicate detection from videos based on trajectories of feature points
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VideoSense: towards effective online video advertising
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A confidence based recognition system for TV commercial extraction
ADC '08 Proceedings of the nineteenth conference on Australasian database - Volume 75
Scene duplicate detection based on the pattern of discontinuities in feature point trajectories
MM '08 Proceedings of the 16th ACM international conference on Multimedia
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Consumer video retargeting: context assisted spatial-temporal grid optimization
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Linking video ads with product or service information by web search
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
VideoSense: a contextual in-video advertising system
IEEE Transactions on Circuits and Systems for Video Technology
A temporal and visual analysis-based approach to commercial detection in news video
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
Video copy detection using multiple visual cues and MPEG-7 descriptors
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Interactive service recommendation based on ad concept hierarchy
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Efficient advertisement discovery for audio podcast content using candidate segmentation
EURASIP Journal on Audio, Speech, and Music Processing
A TV commercial detection system
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
AdVR: linking ad video with products or service
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
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TV advertising is ubiquitous, perseverant, and economically vital. Millions of people's living and working habits are affected by TV commercials. In this paper, we present a multimodal ("visual + audio + text") commercial video digest scheme to segment individual commercials and carry out semantic content analysis within a detected commercial segment from TV streams.Two challenging issues are addressed. Firstly, we propose a multimodal approach to robustly detect the boundaries of individual commercials. Secondly, we attempt to classify a commercial with respect to advertised products/services. For the first, the boundary detection of individual commercials is reduced to the problem of binary classification of shot boundaries via the mid-level features derived from two concepts: Image Frames Marked with Product Information (FMPI) and Audio Scene Change Indicator (ASCI). Moreover, the accurate individual boundary enables us to perform commercial identification by clip matching via a spatial-temporal signature. For the second, commercial classification is formulated as the task of text categorization by expanding sparse texts from ASR/OCR with external knowledge. Our boundary detection has achieved a good result of F1 = 93.7% on the dataset comprising 499 individual commercials from TRECVID'05 video corpus. Commercial classification has obtained a promising accuracy of 80.9% on 141 distinct ones. Based on these achievements, various applications such as an intelligent digital TV set-top box can be accomplished to enhance the TV viewer's capabilities in monitoring and managing commercials from TV streams.