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Fast face recognition by using an inverted index

 
: Herrmann, C.

:
Volltext urn:nbn:de:0011-n-3667468 (318 KByte PDF)
MD5 Fingerprint: 041a4b3b02838665899abb90b128cd2b
Erstellt am: 19.11.2015


Beyerer, Jürgen (Ed.); Pak, Alexey (Ed.):
Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory 2014. Proceedings : July, 20 to 26, 2014; Triberg-Nussbach in Germany
Karlsruhe: KIT Scientific Publishing, 2015 (Karlsruher Schriften zur Anthropomatik 20)
ISBN: 978-3-7315-0401-6
DOI: 10.5445/KSP/1000047712
S.13-23
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation and Institute for Anthropomatics, Vision and Fusion Laboratory (Joint Workshop) <2014, Triberg-Nussbach>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Abstract
This report addresses the task of searching for faces in large video datasets. Despite vast progress in the field, face recognition remains a challenge for uncontrolled large scale applications like searching for persons in surveillance footage or internet videos. While current productive systems focus on the best shot approach, where only one representative frame from a given face track is selected, thus sacrificing recognition performance, systems achieving state-of-the-art recognition performance, like the recently published DeepFace [TYRW14], ignore recognition speed, which makes them impractical for large scale applications. We suggest a set of measures to address the problem. First, considering the feature location allows collecting the extracted features in according sets. Secondly, the inverted index approach, which became popular in the area of image retrieval, is applied to these feature sets. A face track is thus described by a set of local indexed visual words which enables a fast search. In this way, all information from a face track is collected which allows better recognition performance than best shot approaches and the inverted index permits constantly high recognition speeds. Evaluation on a dataset of several thousand videos shows the validity of the proposed approach.

: http://publica.fraunhofer.de/dokumente/N-366746.html