Report on the FG 2015 Video Person Recognition Evaluation

Beveridge, JR; Zhang, H; Draper, BA; Flynn, PJ; Feng, Z; Huber, P; Kittler, J; Huang, Z; Li, S; Li, Y; Kan, M; Wang, R; Shan, S; Chen, X; Li, H; Hua, G; Struc, V; Krizaj, J; Ding, C; Tao, D; Phillips, PJ

Report on the FG 2015 Video Person Recognition Evaluation

Beveridge, JR Zhang, H Draper, BA Flynn, PJ Feng, Z Huber, P Kittler, J Huang, Z Li, S Li, Y Kan, M Wang, R Shan, S Chen, X Li, H Hua, G Struc, V Krizaj, J Ding, C Tao, D

Phillips, PJ

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Publication Type:: Conference Proceeding
Citation:: 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015, 2015
Issue Date:: 2015-07-17

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Field	Value	Language
dc.contributor.author	Beveridge, JR	en_US
dc.contributor.author	Zhang, H	en_US
dc.contributor.author	Draper, BA	en_US
dc.contributor.author	Flynn, PJ	en_US
dc.contributor.author	Feng, Z	en_US
dc.contributor.author	Huber, P	en_US
dc.contributor.author	Kittler, J	en_US
dc.contributor.author	Huang, Z	en_US
dc.contributor.author	Li, S	en_US
dc.contributor.author	Li, Y	en_US
dc.contributor.author	Kan, M	en_US
dc.contributor.author	Wang, R	en_US
dc.contributor.author	Shan, S	en_US
dc.contributor.author	Chen, X	en_US
dc.contributor.author	Li, H	en_US
dc.contributor.author	Hua, G	en_US
dc.contributor.author	Struc, V	en_US
dc.contributor.author	Krizaj, J	en_US
dc.contributor.author	Ding, C	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Phillips, PJ	en_US
dc.date.issued	2015-07-17	en_US
dc.identifier.citation	2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015, 2015	en_US
dc.identifier.isbn	9781479960262	en_US
dc.identifier.uri	http://hdl.handle.net/10453/43294
dc.description.abstract	© 2015 IEEE. This report presents results from the Video Person Recognition Evaluation held in conjunction with the 11th IEEE International Conference on Automatic Face and Gesture Recognition. Two experiments required algorithms to recognize people in videos from the Point-and-Shoot Face Recognition Challenge Problem (PaSC). The first consisted of videos from a tripod mounted high quality video camera. The second contained videos acquired from 5 different handheld video cameras. There were 1401 videos in each experiment of 265 subjects. The subjects, the scenes, and the actions carried out by the people are the same in both experiments. Five groups from around the world participated in the evaluation. The video handheld experiment was included in the International Joint Conference on Biometrics (IJCB) 2014 Handheld Video Face and Person Recognition Competition. The top verification rate from this evaluation is double that of the top performer in the IJCB competition. Analysis shows that the factor most effecting algorithm performance is the combination of location and action: where the video was acquired and what the person was doing.	en_US
dc.relation.ispartof	2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015	en_US
dc.relation.isbasedon	10.1109/FG.2015.7163156	en_US
dc.title	Report on the FG 2015 Video Person Recognition Evaluation	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2015 IEEE. This report presents results from the Video Person Recognition Evaluation held in conjunction with the 11th IEEE International Conference on Automatic Face and Gesture Recognition. Two experiments required algorithms to recognize people in videos from the Point-and-Shoot Face Recognition Challenge Problem (PaSC). The first consisted of videos from a tripod mounted high quality video camera. The second contained videos acquired from 5 different handheld video cameras. There were 1401 videos in each experiment of 265 subjects. The subjects, the scenes, and the actions carried out by the people are the same in both experiments. Five groups from around the world participated in the evaluation. The video handheld experiment was included in the International Joint Conference on Biometrics (IJCB) 2014 Handheld Video Face and Person Recognition Competition. The top verification rate from this evaluation is double that of the top performer in the IJCB competition. Analysis shows that the factor most effecting algorithm performance is the combination of location and action: where the video was acquired and what the person was doing.

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http://hdl.handle.net/10453/43294