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Learning to Identify TV News Monologues by Style and Context
In: DTIC (2003)
Abstract: This research focused on the problem of learning semantics from multimedia data associated with broadcast video documents. The authors proposed to learn semantic concepts from multimodal sources based on style and context detectors, in combination with statistical classifier ensembles. As a case study, they present their method for detecting the concept of news subject monologues. This approach had the best average precision performance amongst 26 submissions in the 2003 video track of the Text Retrieval Conference benchmark. Experiments were conducted with respect to individual detector contribution, ensemble size, and ranking mechanism. It was found that the combination of detectors is decisive for the final result, although some detectors might appear useless in isolation. Moreover, by using a probabilistic ranking in combination with a large classifier ensemble, the results can be improved even further. ; Sponsored in part by the National Science Foundation under Cooperative Agreement No. NSF-IRI-9817496. Prepared in cooperation with the Dutch ICES/KIS Multimedia Information Analysis project and TNO Institute of Applied Physics, Delft, The Netherlands. The original document contains color images.
Keyword: *AUTOMATION; *DETECTION; *DIGITAL RECORDING SYSTEMS; *FEATURE EXTRACTION; *MULTIMODE; *NEWS BROADCASTING; *PATTERN RECOGNITION; *TELEVISION BROADCASTING; *VIDEO RECORDING; *VIDEO RETRIEVAL; ARTIFICIAL INTELLIGENCE; AUTOMATIC INDEXING; BROADCAST NEWS VIDEO; CASE STUDIES; CLASSIFICATION; CLASSIFIER ENSEMBLES; CONTENT ANALYSIS; CONTEXT DETECTORS; Cybernetics; DIGITAL VIDEOS; FACE RECOGNITION; FACIAL FEATURES; Information Science; LEARNING MACHINES; Linguistics; MACHINE AIDED INDEXING; MULTIMODAL ANALYSIS; MULTIMODAL PEOPLE DETECTION; NEWS SUBJECT MONOLOGUES; PROBABILITY; RANKING; Recording and Playback Devices; SEMANTIC LEARNING; SEMANTICS; SPEAKER FEATURES; SPEECH TRANSCRIPT FEATURES; STATISTICAL ANALYSIS; STATISTICAL CLASSIFICATION; STYLE DETECTORS; TELEVISION SYSTEMS; TRECVID BENCHMARK; TV BROADCASTING; VIDEO INDEXING
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA458538
http://www.dtic.mil/docs/citations/ADA458538
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