Semantic Indexing of Multimedia Content Using Visual, Audio, and Text Cues
نویسندگان
چکیده
منابع مشابه
Semantic indexing of multimedia using audio, text and visual cues
In this paper we describe methods for automatic labeling of highlevel semantic concepts in documentary style videos. The emphasis of this paper is on audio processing and on fusing information from multiple modalities. The work described represents initial work towards a trainable system that acquires a collection of generic “intermediate” semantic concepts across modalities (such as audio, vid...
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We present a learning-based approach to the semantic indexing of multimedia content using cues derived from audio, visual, and text features. We approach the problem by developing a set of statistical models for a predefined lexicon. Novel concepts are then mapped in terms of the concepts in the lexicon. To achieve robust detection of concepts, we exploit features from multiple modalities, name...
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Indexing and retrieving audio or video content presents challenges specific to the nature of these media. Two primary difficulties are the inaccuracy of speech recognition and the timed nature of streaming media — that is, the property that words and other information in audio/video are tied to times, and are not readily accessed and scanned at arbitrary positions. StreamSage's approach to reso...
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MUVIS is a collaborative framework that supports indexing, browsing and querying of various multimedia types such as audio, video, audio/video interlaced in several formats. It allows real-time audio and video capturing, encoding by last generation codecs such as MPEG-4, H.263+, MP3 and AAC. MUVIS also supports several audio/video file format such as AVI, MP4, MP3 and AAC. MUVIS achieves a glob...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2003
ISSN: 1687-6180
DOI: 10.1155/s1110865703211173