Content-Based Video Retrieval: A Database PerspectiveSpringer Science & Business Media, 2013. gada 29. jūn. - 151 lappuses The area of content-based video retrieval is a very hot area both for research and for commercial applications. In order to design effective video databases for applications such as digital libraries, video production, and a variety of Internet applications, there is a great need to develop effective techniques for content-based video retrieval. One of the main issues in this area of research is how to bridge the semantic gap between low-Ievel features extracted from a video (such as color, texture, shape, motion, and others) and semantics that describe video concept on a higher level. In this book, Dr. Milan Petkovi6 and Prof. Dr. Willem Jonker have addressed this issue by developing and describing several innovative techniques to bridge the semantic gap. The main contribution of their research, which is the core of the book, is the development of three techniques for bridging the semantic gap: (1) a technique that uses the spatio-temporal extension of the Cobra framework, (2) a technique based on hidden Markov models, and (3) a technique based on Bayesian belief networks. To evaluate performance of these techniques, the authors have conducted a number of experiments using real video data. The book also discusses domains solutions versus general solution of the problem. Petkovi6 and Jonker proposed a solution that allows a system to be applied in multiple domains with minimal adjustments. They also designed and described a prototype video database management system, which is based on techniques they proposed in the book. |
No grāmatas satura
1.–5. rezultāts no 25.
. lappuse
... video libraries , because of the obvious difference in the nature of the documents in video on the one hand , and text collections on the other hand . Instead of words , a video retrieval system deals with collections of video records ...
... video libraries , because of the obvious difference in the nature of the documents in video on the one hand , and text collections on the other hand . Instead of words , a video retrieval system deals with collections of video records ...
2. lappuse
... documents in the same way as a database management system does with alphanumerical data . As video data is different from alphanumeric data ( multiple modalities , ambiguity of interpretation , voluminous nature , etc. ) , it is far ...
... documents in the same way as a database management system does with alphanumerical data . As video data is different from alphanumeric data ( multiple modalities , ambiguity of interpretation , voluminous nature , etc. ) , it is far ...
3. lappuse
... video retrieval problem lies at the crossroads among many fields and cannot ... video retrieval systems that will be surveyed in chapters 2 and 3 , and , on the ... document . A video model should represent the content of these modalities ...
... video retrieval problem lies at the crossroads among many fields and cannot ... video retrieval systems that will be surveyed in chapters 2 and 3 , and , on the ... document . A video model should represent the content of these modalities ...
9. lappuse
... documents . However , with further emergence of the Web and multimedia the importance of systems that can manage and search audio - visual data has arisen . This chapter provides an introduction to databases , information retrieval ...
... documents . However , with further emergence of the Web and multimedia the importance of systems that can manage and search audio - visual data has arisen . This chapter provides an introduction to databases , information retrieval ...
18. lappuse
Esat sasniedzis šīs grāmatas aplūkošanas reižu limitu.
Esat sasniedzis šīs grāmatas aplūkošanas reižu limitu.
Saturs
Database Management Systems and ConetentBased Retrieval | 31 |
SpatioTemporal Formalization of Video Events 55 | 54 |
Stochastic Modeling of Video Events | 73 |
A Prototype of a Video DBMS 109 | 108 |
Conclusions | 141 |
About the Authors | 149 |
Citi izdevumi - Skatīt visu
Content-Based Video Retrieval: A Database Perspective Milan Petković,Willem Jonker Ierobežota priekšskatīšana - 2003 |
Content-Based Video Retrieval: A Database Perspective Milan Petković,Willem Jonker Priekšskatījums nav pieejams - 2013 |
Content-Based Video Retrieval: A Database Perspective Milan Petković,Willem Jonker Priekšskatījums nav pieejams - 2010 |
Bieži izmantoti vārdi un frāzes
algebra algorithm annotation approach architecture audio-visual Australian Open automatic extraction chapter Cobra framework Cobra video codebook color histogram computer vision content-based retrieval content-based video retrieval data model database management system database system DBMS defined described detection dominant color dynamic Bayesian networks evaluation event descriptions event type example feature extraction feature grammar frames hidden Markov models high-level concepts highlights implementation information retrieval integrated interface intervals low-level features Matlab metadata MFCC Michael Schumacher modalities Monet movie Multimedia net-playing object grammar objects and events observation sequence operations performed physical level pixels prototype quantization query language raw video data regions schema Section semantic content semantic gap spatial spatio-temporal formalization specific stroke recognition techniques temporal relations Tennis case study tennis videos video content video database management video documents video modeling video objects video processing video retrieval system video sequences video structure video units