DocumentCode
33778
Title
A Fair Comparison Should Be Based on the Same Protocol--Comments on "Trainable Convolution Filters and Their Application to Face Recognition"
Author
Liang Chen
Author_Institution
Coll. of Math. & Inf. Sci., Wenzhou Univ. (adjunct), Wenzhou, China
Volume
36
Issue
3
fYear
2014
fDate
Mar-14
Firstpage
622
Lastpage
623
Abstract
We comment on a paper describing an image classification approach called Volterra kernel classifier, which was called Volterrafaces when applied to face recognition. The performances were evaluated by the experiments on face recognition databases. We find that their comparisons with the state of the art of three databases were indeed based on unfair settings. The results with the settings of the standard protocol on three data sets are generated, which show that Volterrafaces achieves the state-of-the-art performance only in one database.
Keywords
convolution; face recognition; filtering theory; image classification; visual databases; Volterra kernel classifier; Volterrafaces; face recognition databases; image classification approach; trainable convolution filter; Computer vision; Face recognition; Kernel; Protocols; Standards; Training; Face recognition; Volterra kernels; Volterrafaces; filtering classifier;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.2013.187
Filename
6616538
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