Fast face recognition by using an inverted index

Christian Herrmann; Jürgen Beyerer

doi:10.1117/12.2078988

27 February 2015 Fast face recognition by using an inverted index

Christian Herrmann, Jürgen Beyerer

Proceedings Volume 9405, Image Processing: Machine Vision Applications VIII; 940507 (2015) https://doi.org/10.1117/12.2078988
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

This contribution 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, 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. 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.

Citation Download Citation

Christian Herrmann and Jürgen Beyerer "Fast face recognition by using an inverted index", Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 940507 (27 February 2015); https://doi.org/10.1117/12.2078988

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