In recent years face recognition has made extraordinary leaps, yet unconstrained video-based face identification in the wild remains an open and interesting problem. Videos, unlike still-images, offer a myriad of data for face modeling, sampling, and recognition, but, on the other hand, contain low-quality frames and motion blur. A key component in video-based face recognition is the way in which faces are associated through the video sequence before being used for recognition. In this paper, we present a video-based face recognition method taking advantage of face and body association (FBA). To track and associate subjects that appear across frames in multiple shots, we solve a data association problem using both face and body appearance. The final recovered track is then used to build a face representation for recognition. We evaluate our FBA method for video-based face recognition on a challenging

Face and Body Association for Video-based Face Recognition / Kim, K; Yang, Z; Masi, I; Nevatia, R; Medioni, G. - (2018). ((Intervento presentato al convegno Winter Conference on Applications of Computer Vision (WACV) tenutosi a Lake Tahoe.

Face and Body Association for Video-based Face Recognition

Masi I;
2018

Abstract

In recent years face recognition has made extraordinary leaps, yet unconstrained video-based face identification in the wild remains an open and interesting problem. Videos, unlike still-images, offer a myriad of data for face modeling, sampling, and recognition, but, on the other hand, contain low-quality frames and motion blur. A key component in video-based face recognition is the way in which faces are associated through the video sequence before being used for recognition. In this paper, we present a video-based face recognition method taking advantage of face and body association (FBA). To track and associate subjects that appear across frames in multiple shots, we solve a data association problem using both face and body appearance. The final recovered track is then used to build a face representation for recognition. We evaluate our FBA method for video-based face recognition on a challenging
Winter Conference on Applications of Computer Vision (WACV)
face recognition, deep learning, face analysis
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Face and Body Association for Video-based Face Recognition / Kim, K; Yang, Z; Masi, I; Nevatia, R; Medioni, G. - (2018). ((Intervento presentato al convegno Winter Conference on Applications of Computer Vision (WACV) tenutosi a Lake Tahoe.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1458950
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