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Download Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing (The Springer International Series in Engineering and Computer Science) eBook

by Tong Zhang,C.C. Jay Kuo

Download Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing (The Springer International Series in Engineering and Computer Science) eBook
ISBN:
0792372875
Author:
Tong Zhang,C.C. Jay Kuo
Category:
Networking & Cloud Computing
Language:
English
Publisher:
Springer; 2001 edition (January 31, 2001)
Pages:
136 pages
EPUB book:
1987 kb
FB2 book:
1397 kb
DJVU:
1134 kb
Other formats
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Rating:
4.5
Votes:
506


Included is extensive treatment of audiovisual data segmentation, indexing and retrieval based on multimodal . The developing MPEG-7 standards are explored

Included is extensive treatment of audiovisual data segmentation, indexing and retrieval based on multimodal media content analysis, and content-based. The developing MPEG-7 standards are explored. Show all. Table of contents (8 chapters).

Included is extensive treatment of audiovisual data segmentation.

FREE shipping on qualifying offers. Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing is an up-to-date overview of audio and video content analysis. Included is extensive treatment of audiovisual data segmentation.

Jay Kuo. Included is extensive treatment of audiovisual data segmentation, indexing and retrieval based on multimodal media content analysis, and content-based management of audio data. In addition to the commonly studied audio types such as speech and music, the authors have included hybrid types of sounds that contain more than one kind of audio component such as speech or environmental sound with music in the background.

series The Springer International Series in Engineering and Computer Science

series The Springer International Series in Engineering and Computer Science Included is extensive treatment of audiovisual data segmentation, indexing and retrieval based on multimodal media content analysis, and content-based management of audio data. Emphasis is also placed on semantic-level identification and classification of environmental sounds.

oceedings{dAC, title {Content-Based Audio Classification and Retrieval for . 2. Video Content Modeling. 3. Audio Feature Analysis. 4. Generic Audio Data Segmentation and Indexing. 5. Sound Effects Classification and Retrieval.

oceedings{dAC, title {Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing}, author {Tong Zhang and Che Chun Kuo}, year {2001} }. Tong Zhang, Che Chun Kuo. Published 2001. 6. Image Sequence Analysis. 7. Experimental Results. 8. Conclusion and Extensions.

Included is extensive treatment of audiovisual data segmentation, indexing and retrieval based on multimodal media content analysis, and content-based management of audio data.

PDF Many commonly applied audio features suffer from certain limitations in describing the data content for classification and retrieval purposes.

2) Content-Based Audio Retrieval: One specific technique in. .

2) Content-Based Audio Retrieval: One specific technique in content-based audio retrieval is query-by-humming, through which a song is retrieved by humming the tune of it. A typical system was presented by Ghias et al. for this purpose. Finally, the proposed audio segmentation and classification approach is based on the observation of different types of audio signals and their physical features, which is generic and modelfree.

This book serves as an invaluable reference with respect to the most important standards in the field. Video and Image Processing in Multimedia Systems is suitable as a textbook for course use. Скачать (pdf, . 0 Mb) Читать. Epub FB2 mobi txt RTF.

Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing is an up-to-date overview of audio and video content analysis. Included is extensive treatment of audiovisual data segmentation, indexing and retrieval based on multimodal media content analysis, and content-based management of audio data. In addition to the commonly studied audio types such as speech and music, the authors have included hybrid types of sounds that contain more than one kind of audio component such as speech or environmental sound with music in the background. Emphasis is also placed on semantic-level identification and classification of environmental sounds. The authors introduce a new generic audio retrieval system on top of the audio archiving schemes. Both theoretical analysis and implementation issues are presented. The developing MPEG-7 standards are explored. Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing will be especially useful to researchers and graduate level students designing and developing fully functional audiovisual systems for audio/video content parsing of multimedia streams.