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Output details

11 - Computer Science and Informatics

Queen Mary University of London

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Output 7 of 83 in the submission

Article title

Adaptive Online Performance Evaluation of Video Trackers

Type

D - Journal article

DOI

10.1109/TIP.2011.2182520

Title of journal

IEEE Transactions on Image Processing

Article number

Volume number

Issue number

First page of article

2812

ISSN of journal

1941-0042

Year of publication

2012

URL

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6121948

Number of additional authors

Additional information

<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.

Interdisciplinary

Cross-referral requested

Research group

None

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract