| 000 | 00000cam u2200205 a 4500 | |
| 001 | 000045912480 | |
| 005 | 20170818180231 | |
| 008 | 170817s2003 maua b 101 0 eng d | |
| 010 | ▼a 2003054989 | |
| 020 | ▼a 1402075499 | |
| 035 | ▼a (KERIS)REF000007360171 | |
| 040 | ▼a DLC ▼c DLC ▼d DLC ▼d 211009 | |
| 050 | 0 0 | ▼a QA76.9.D343 ▼b D56 2002 |
| 082 | 0 0 | ▼a 006.3 ▼2 23 |
| 084 | ▼a 006.3 ▼2 DDCK | |
| 090 | ▼a 006.3 ▼b V652 | |
| 245 | 0 0 | ▼a Video mining / ▼c edited by Azriel Rosenfeld, David Doermann, Daniel DeMenthon. |
| 260 | ▼a Boston : ▼b Kluwer Academic, ▼c c2003. | |
| 300 | ▼a viii, 340 p. : ▼b ill. ; ▼c 25 cm. | |
| 490 | 1 | ▼a The Kluwer international series in video computing |
| 500 | ▼a Expansions of selected papers that were presented at the DIMACS Workshop on Video Mining, held November 4-6, 2002 at Rutgers University in Piscataway, NJ. | |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Multimedia data mining ▼v Congresses. |
| 700 | 1 | ▼a Rosenfeld, Azriel, ▼d 1931-. |
| 700 | 1 | ▼a Doermann, David S. ▼q (David Scott). |
| 700 | 1 | ▼a DeMenthon, Daniel. |
| 711 | 2 | ▼a DIMACS Workshop on Video Mining ▼d (2002 : ▼c Rutgers University). |
| 830 | 0 | ▼a Kluwer international series in video computing. |
| 945 | ▼a KLPA |
Holdings Information
| No. | Location | Call Number | Accession No. | Availability | Due Date | Make a Reservation | Service |
|---|---|---|---|---|---|---|---|
| No. 1 | Location Main Library/Western Books/ | Call Number 006.3 V652 | Accession No. 111777392 | Availability Available | Due Date | Make a Reservation | Service |
Contents information
Table of Contents
Contents 1. Efficient Video Browsing 2. Beyond Key-Frames: The Physical Setting as a Video Mining Primitive 3. Temporal Video Boundaries 4. Video Summarization using MPEG-7 Motion Activity and Audio Descriptors 5. Movie Content Analysis, Indexing and Skimming Via Multimodal Information 6. Video OCR: A Survey and Practitioner''s Guide 7. Video Categorization Using Semantics and Semiotics 8. Understanding the Semantics of Media 9. Statistical Techniques for Video Analysis and Searching 10. Mining Statistical Video Structures 11. Pseudo-Relevance Feedback for Multimedia Retrieval Index.