TY - GEN
T1 - Single sample face recognition from video via stacked supervised auto-encoder
AU - Vega, Pedro J.Soto
AU - Feitosa, Raul Queiroz
AU - Quirita, Victor H.Ayma
AU - Happ, Patrick Nigri
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/10
Y1 - 2017/1/10
N2 - This work proposes and evaluates strategies based on Stacked Supervised Auto-Encoders (SSAE) for face representation in video surveillance applications. The study focuses on the identification task with a single sample per person (SSPP) in the gallery. Variations in terms of pose, facial expression, illumination and occlusion are approached in two ways. First, the SSAE extracts features from face images, which are robust to such variations. Second, we propose methods to exploit the multiple samples per persons probes (MSPPP) that can be extracted from video sequences. Three variants of the proposed method are compared upon HONDA/UCSD and VIDTIMIT video datasets. The experimental results demonstrate that strategies combining SSAE and MSPPP are able to outperform other SSPP methods, such a local binary patterns, in face recognition from video.
AB - This work proposes and evaluates strategies based on Stacked Supervised Auto-Encoders (SSAE) for face representation in video surveillance applications. The study focuses on the identification task with a single sample per person (SSPP) in the gallery. Variations in terms of pose, facial expression, illumination and occlusion are approached in two ways. First, the SSAE extracts features from face images, which are robust to such variations. Second, we propose methods to exploit the multiple samples per persons probes (MSPPP) that can be extracted from video sequences. Three variants of the proposed method are compared upon HONDA/UCSD and VIDTIMIT video datasets. The experimental results demonstrate that strategies combining SSAE and MSPPP are able to outperform other SSPP methods, such a local binary patterns, in face recognition from video.
KW - Auto-encoder
KW - Face Recognition
KW - Surveillance
UR - http://www.scopus.com/inward/record.url?scp=85013746162&partnerID=8YFLogxK
U2 - 10.1109/SIBGRAPI.2016.022
DO - 10.1109/SIBGRAPI.2016.022
M3 - Articulo (Contribución a conferencia)
AN - SCOPUS:85013746162
T3 - Proceedings - 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2016
SP - 96
EP - 103
BT - Proceedings - 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 October 2016 through 7 October 2016
ER -