Content-based indexing of image and video databases by global and shape features
- 1 January 1996
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 3, 140-144 vol.3
- https://doi.org/10.1109/icpr.1996.546810
Abstract
Indexing and retrieval methods based on the image content are required to effectively use information from the large repositories of digital images and videos currently available. Both global (colour, texture, motion, etc.) and local (object shape, etc.) features are needed to perform a reliable content based retrieval. We present a method for automatic extraction of global image features, like colour and motion parameters, and their use for data restriction in video database querying. Further retrieval is therefore accomplished, in a restricted set of images, by shape feature (skeleton, local symmetry moments, correlation, etc.) local search. The proposed indexing methodology has been developed and tested inside JACOB, a prototypal system for content-based video database querying.Keywords
This publication has 10 references indexed in Scilit:
- JACOB: just a content-based query system for video databasesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Motion and color-based video indexing and retrievalPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1996
- Query by image and video content: the QBIC systemComputer, 1995
- Query by image example: the comparison algorithm for navigating digital image databases (CANDID) approachPublished by SPIE-Intl Soc Optical Eng ,1995
- Shape analysis for image retrievalPublished by SPIE-Intl Soc Optical Eng ,1994
- Performance of optical flow techniquesInternational Journal of Computer Vision, 1994
- Digital video segmentationPublished by Association for Computing Machinery (ACM) ,1994
- The intensity axis of symmetry and its application to image segmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1993
- A visual information management system for the interactive retrieval of facesIEEE Transactions on Knowledge and Data Engineering, 1993
- On the estimation of optical flow: Relations between different approaches and some new resultsArtificial Intelligence, 1987