Output details
11 - Computer Science and Informatics
Queen Mary University of London
Adaptive Online Performance Evaluation of Video Trackers
<23>The performance of video trackers depends on the setting in which they are used. This paper supports the testing and evaluation of different trackers using long sequences of raw in situ data. This work on performance self-evaluation has led to two separate invitations to join application-oriented projects: an ARTEMIS (www.artemis.eu/) Joint Undertaking Industry project (332913; 2013-2016) on Cognitive & Perceptive CAMeraS (Christian Fabre, christian.fabre1@cea.fr) in which the ideas are being used in a new sensor platform, and a new collaboration with Honeywell (Dr. Vit Libal, Vit.Libal@Honeywell.com) resulting in an Industry-Academia partnership (IAPP-324359; 2013-2016) for scene monitoring and activity understanding.