Output details
13 - Electrical and Electronic Engineering, Metallurgy and Materials
Queen Mary University of London : A - Electrical and Electronic engineering
Article title
Coupled prediction classification for robust visual tracking.
Type
D - Journal article
Title of journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
Article number
-
Volume number
32
Issue number
9
First page of article
1553
ISSN of journal
1939-3539
Year of publication
2010
Number of additional authors
1
Additional information
This paper addresses two of the most important problems in visual tracking, namely large motions and occlusions and expresses, in a unified framework, generative and discriminative approaches. The method is shown to significantly outperform other methods in the literature in challenging sequences. This is in collaboration with Professor Hancock from University of York. This work supported EPSRC-grant (EP/G033935/1, "Localisation and Recognition of Human actions in Image Sequences", £340k, 2009-2012).
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
