Information Retrieval Techniques for non-textual media - Prof. A ...

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Notable works • Multimedia Information Retrieval Systems • Applications of video-content analysis and retrieval • Intelligent Multimedia Information Retrieval • Content-based multimedia information retrieval: • Content based image retrieval were some of the works done on these areas.
THE MULTIMEDIA ANALYSIS AND RETRIEVAL SYSTEM • The Multimedia Analysis and Retrieval System (MARS) was developed by Sharad Mehrotra of the Department of Information and Computer Science, University of California. • The goals of the MARS project are to design and develop an integrated multimedia information retrieval and database management infrastructure, entitled Multimedia Analysis and Retrieval System (MARS), that supports multimedia information as firstclass objects suited for storage and retrieval based on their content.
Page 1 and 2: INFORMATION RETRIEVAL TECHNIQUES FO
Page 3 and 4: Media Storage • Ninety-two percen
Page 5 and 6: Population Reference Bureau • the
Page 7 and 8: The WWW • contains about 170 tera
Page 9 and 10: Web content • The median size of
Page 11 and 12: AVI & mp3 files • In looking at f
Page 13 and 14: Growth of multimedia content • Th
Page 15 and 16: Databases • Collection of all org
Page 17 and 18: Metadata • The word Metadata is u
Page 19: Types of Search Queries • Most of
Page 23 and 24: Information Retrieval Systems (IRS)
Page 25 and 26: Ways of locating text documents •
Page 33 and 34: MIMD architectures • Document /da
Page 36 and 37: Multimedia Mining Hierarchy • Mul
Page 38 and 39: Image-based Applications • due to
Page 40 and 41: Images • Images offer a number of
Page 42 and 43: Characteristics of original image c
Page 44 and 45: The elements used for image represe
Page 46 and 47: Image retrieval queries • can be
Page 48 and 49: Text-based image retrieval : • Of
Page 50 and 51: • Currently, CBIR routines are re
Page 52 and 53: Basic color profile • Though ther
Page 54 and 55: Automatic object recognition • To
Page 56 and 57: Automatic Linguistic Indexing of Pi
Page 60 and 61: Streamed media applications: Source
Page 62 and 63: Streamed-data applications include
Page 64 and 65: Search requests for streamed data
Page 66 and 67: Web Server vs. Streaming Server: CE
Page 68 and 69: Watch Live programmes
Page 70 and 71:
• This media file is then placed
Page 72 and 73:
Data Delivery • The rest of the s
Page 74 and 75:
• For example, • One hour of vi
Page 76 and 77:
Protocol issues • five major type
Page 78 and 79:
Unicast protocols • send a separa
Page 80 and 81:
Benefits of protocols • UDP - pro
Page 82 and 83:
Vlc media player options
Page 84 and 85:
Inputs VLC features page UDP Unicas
Page 86 and 87:
Web 2.0 Ogg bitstream format • Fr
Page 88 and 89:
Internet television: (ERNET Model)
Page 90 and 91:
P2PTV • The term P2PTV refers to
Page 92 and 93:
• The benefits of using PeerCast
Page 94 and 95:
• Supported live media sources in
Page 96 and 97:
Decoded capture • An approach use
Page 98 and 99:
• International Institute of Info
Page 100 and 101:
Music Information Retrieval • to
Page 102 and 103:
Content-based music retrieval using
Page 104 and 105:
Flash video + text + command button
Page 106 and 107:
E-content deployment • Full conte
Page 108 and 109:
LOR: Front page- Blocked content
Page 110 and 111:
Radio Broadcast TV Broadcast Videoc
Page 112:
Thank you
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