ProVeR: Probabilistic Video Retrieval using the Gauss-Tree

Modeling objects by probability density functions (pdf) is a new powerful method to represent complex objects in databases. By representing an object as a pdf, e.g. a Gaussian, it is possible to represent very large and complex objects in a compact and still descriptive way. In this contribution, we propose ProVeR a prototype search engine for content-based video retrieval which represents a video as a set of Gaussians. The Gaussians are managed by the Gauss-tree, an index structure allowing the efficient processing of probabilistic queries. ProVeR provides even non-expert users with an intuitive method for efficient, content-based retrieval of videos containing similar shots and scenes.

• Type: Conference
• Year: 2007
• Where: ICDE
• Authors: Alexey Pryakhin, Christian Böhm, Matthias Schubert, Michael Gruber, Peter Kunath
• Keywords: Complex Objects, Content-based Retrieval, Content-based Video Retrieval, Database, ICDE 2007