Name
Title | ||
|---|---|---|
Content Classification of Multimedia Documents using Partitions of Low-Level Features |
Abstract | ||
|---|---|---|
Audio-visual documents obtained from German TV news are classified according to the IPTC topic cat- egorization scheme. To this end usual text classifi- cation techniques are adapted to speech, video, and non-speech audio. For each of the three modalities word analogues are generated: sequences of syllables for speech, "video words" based on low level color features (color moments, color correlogram and color wavelet), and "audio words" based on low-level spec- tral features (spectral envelope and spectral flatness) for non-speech audio. Such audio and video words provide a means to represent the different modalities in a uniform way. The frequencies of the word analogues represent audio-visual documents: the standard bag- |
Year | Venue | Keywords |
|---|---|---|
2006 | JVRB | speech recognition,integration of modalities.,sup- port vector machines,audio-visual content classification |
DocType | Volume | Citations |
Journal | 3 | 1 |
PageRank | References | Authors |
0.39 | 11 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edda Leopold | 1 | 381 | 30.50 |
| Schloss Birlinghoven | 2 | 8 | 2.83 |