Open Access
A feature database for multimedia objects
Martin L. Kersten,Niels Nes,Menzo Windhouwer +2 more
- 31 Dec 1998
- Iss: 7, pp 1-10
TL;DR: An overview of the Acoi architecture and the Feature Detector Engine (FDE) model is provided to facilitate studies in the area of indexing multimedia objects and their subsequent retrieval.
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Abstract: The Acoi project provides a large-scale experimentation platform to facilitate studies in the area of indexing multimedia objects and their subsequent retrieval. The index model is based on assembling the results of feature detection algorithms into hierarchical structures to classify the objects. This paper provides an overview of the Acoi architecture and the Feature Detector Engine (FDE) model. Central to its design is a grammatical description of the feature relations to classify the multimedia objects and to steer their detection and storage. Its role is informally introduced.
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Citations
Feature grammar systems. Incremental maintenance of indexes to digital media warehouses
M.A. Windhouwer
- 01 Nov 2003
TL;DR: This paper aims to provide a history of parsing algorithms and procedures used in the development of parseragnostic systems for knowledge representation in the contexts of knowledge representation and retrieval.
Patent
Smart-court system and method for providing real-time debriefing and training services of sport games
Chen Shachar,Evgeni Khazanov,Yoram Ben Zur +2 more
- 21 Feb 2013
TL;DR: In this paper, a Smart-court system for real-time analysis and debriefing of sport activities is presented, consisting of an automatic recording system comprising a plurality of video cameras located in a court, arranged to realtime (RT) recording of a sport session and utilizing automatic calibration and stabilization module.
31
Acoi: A system for Indexing Multimedia Objects
Windhouwer,A.R. Schmidt,M.L. Kersten +2 more
- 01 Jan 1999
TL;DR: A SQL-like query language enables users to use the feature grammar as a schema for query formulation to retrieve both index values and the original data sources.
•Proceedings Article
Flexible and scalable digital library search
Henk Ernst Blok,Menzo Windhouwer,Roelof van Zwol,Milan Petkovic,Peter M. G. Apers,Martin L. Kersten,Willem Jonker +6 more
- 11 Sep 2001
TL;DR: The proposed system architecture consists of three levels: the conceptual, the logical and the physical level, which allows the combination of both conceptual and content-based querying in the query stage.
Information access in multimedia databases based on feature models
TL;DR: This work describes the experimentation platform under development, making database technology available to multimedia, based on the new notion of feature databases, and its architecture fully integrates traditional query processing and content-based retrieval techniques.
References
Monet: An Impressionist Sketch of an Advanced Database System
Peter Boncz,Martin L. Kersten +1 more
- 01 Jan 1995
TL;DR: Monet as mentioned in this paper is a customizable database system developed at CWI and University of Amsterdam, intended to be used as the database backend for widely varying application domains and is designed to get maximum database performance out of modern workstations and multiprocessor systems.
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Proceedings of the second ACM international conference on Digital libraries
Robert B. Allen,Edie Rasmussen +1 more
- 01 Jul 1997
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Proceedings of the first ACM international conference on Digital libraries
Edward A. Fox,Gary Marchionini +1 more
- 01 Apr 1996
TL;DR: This document contains papers which were presented at the First ACM International Conference on Digital Libraries and Topics processed for this document included information retrieval and index structures for structured documents.
28
Query by image and video content: the QBIC system
Myron D. Flickner,Harpreet Sawhney,W. Niblack,Jonathan Ashley,Qian Huang,Byron Dom,Monika Gorkani,James Lee Hafner,D. Lee,Dragutin Petkovic,David Steele,Peter Cornelius Yanker +11 more
TL;DR: The Query by Image Content (QBIC) system as discussed by the authors allows queries on large image and video databases based on example images, user-constructed sketches and drawings, selected color and texture patterns, camera and object motion, and other graphical information.
•Proceedings Article
Query by image and video content: the QBIC system
Myron D. Flickner,Harpreet Sawhney,W. Niblack,Jonathan Ashley,Qian Huang,Byron Dom,Monika Gorkani,James Lee Hafner,D. Lee,Dragutin Petkovic,David Steele,Peter Cornelius Yanker +11 more
- 30 May 1997
TL;DR: The Query by Image Content (QBIC) system as mentioned in this paper allows queries on large image and video databases based on example images, user-constructed sketches and drawings, selected color and texture patterns, camera and object motion, and other graphical information.