Annotation Collection and Online Performance Evaluation for Video Surveillance: The ViSOR Project

摘要

This paper presents the Visor (VIdeo Surveillance Online Repository) project designed with the aim of establishing an open platform for collecting, annotating, retrieving, sharing surveillance videos, and of evaluating the performance of automatic surveillance systems. The main idea is to exploit the collaborative paradigm spreading in the web community to join together the ontology based annotation and retrieval concepts and the requirements of the computer vision and video surveillance communities.  The ViSOR open repository is based on a reference ontology which integrates many concepts, also coming from LSCOM and MediaMill ontologies.The web interface allows video browse, query by annotated concepts or by keywords, compressed video preview, media download and upload. The repository contains metadata annotations, which can be either manually created as ground truth or automatically generated by video surveillance systems. Their automatic annotations can be compared each other or with the reference ground-truth exploiting an integrated on-line performance evaluator.