The ijcb 2014 pasc video face and person recognition competition

Ross Beveridge, Hao Zhang, Patrick Flynn, Yooyoung Lee, Venice Erin Liong, Jiwen Lu, Marcus de Assis Angeloni, Tiago de Freitas Pereira, Haoxiang Li, Gang Hua, Vitomir Štruc, Janez Križaj, Jonathon Phillips (2014): The ijcb 2014 pasc video face and person recognition competition. Proceedings of the IEEE International Joint Conference on Biometrics (IJCB), IEEE 2014.

Abstract

The Point-and-Shoot Face Recognition Challenge (PaSC) is a performance evaluation challenge including 1401 videos of 265 people acquired with handheld cameras and depicting people engaged in activities with non-frontal head pose. This report summarizes the results from a competition using this challenge problem. In the Video-to-video Experiment a person in a query video is recognized by comparing the query video to a set of target videos. Both target and query videos are drawn from the same pool of 1401 videos. In the Still-to-video Experiment the person in a query video is to be recognized by comparing the query video to a larger target set consisting of still images. Algorithm performance is characterized by verification rate at a false accept rate of 0:01 and associated receiver operating characteristic (ROC) curves. Participants were provided eye coordinates for video frames. Results were submitted by 4 institutions: (i) Advanced Digital Science Center, Singapore; (ii) CPqD, Brasil; (iii) Stevens Institute of Technology, USA; and (iv) University of Ljubljana, Slovenia. Most competitors demonstrated video face recognition performance superior to the baseline provided with PaSC. The results represent the best performance to date on the handheld video portion of the PaSC.

BibTeX (Download)

@conference{beveridge2014ijcb,
title = {The ijcb 2014 pasc video face and person recognition competition},
author = {Ross Beveridge and Hao Zhang and Patrick Flynn and Yooyoung Lee and Venice Erin Liong and Jiwen Lu and Marcus de Assis Angeloni and Tiago de Freitas Pereira and Haoxiang Li and Gang Hua and Vitomir \v{S}truc and Janez Kri\v{z}aj and Jonathon Phillips},
url = {http://luks.fe.uni-lj.si/nluks/wp-content/uploads/2016/09/IJCB2014.pdf},
year  = {2014},
date = {2014-01-01},
booktitle = {Proceedings of the IEEE International Joint Conference on Biometrics (IJCB)},
pages = {1--8},
organization = {IEEE},
abstract = {The Point-and-Shoot Face Recognition Challenge (PaSC) is a performance evaluation challenge including 1401 videos of 265 people acquired with handheld cameras and depicting people engaged in activities with non-frontal head pose. This report summarizes the results from a competition using this challenge problem. In the Video-to-video Experiment a person in a query video is recognized by comparing the query video to a set of target videos. Both target and query videos are drawn from the same pool of 1401 videos. In the Still-to-video Experiment the person in a query video is to be recognized by comparing the query video to a larger target set consisting of still images. Algorithm performance is characterized by verification rate at a false accept rate of 0:01 and associated receiver operating characteristic (ROC) curves. Participants were provided eye coordinates for video frames. Results were submitted by 4 institutions: (i) Advanced Digital Science Center, Singapore; (ii) CPqD, Brasil; (iii) Stevens Institute of Technology, USA; and (iv) University of Ljubljana, Slovenia. Most competitors demonstrated video face recognition performance superior to the baseline provided with PaSC. The results represent the best performance to date on the handheld video portion of the PaSC.},
keywords = {biometrics, competition, face recognition, group evaluation, IJCB, PaSC, performance evaluation},
pubstate = {published},
tppubtype = {conference}
}