TY - GEN
T1 - Show me your body
T2 - 23rd IEEE International Conference on Image Processing, ICIP 2016
AU - Kakadiaris, Ioannis A.
AU - Sarafianos, Nikolaos
AU - Nikou, Christophoros
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/3
Y1 - 2016/8/3
N2 - In this work, we investigate the problem of predicting gender from still images using human metrology. Since the values of the anthropometric measurements are difficult to be estimated accurately from state-of-the-art computer vision algorithms, ratios of anthropometric measurements were used as features. Additionally, since several measurements will not be available at test time in a real-life scenario, we opted for the Learning Using Privileged Information (LUPI) paradigm. During training, we used as features, ratios from all the available anthropometric measurements, whereas at test time only ratios of measurable (i.e., observable) quantities were used. We show that by using the LUPI framework, the estimation of soft biometric characteristics such as gender is possible. Gender classification from human metrology is also tested on real images with promising results.
AB - In this work, we investigate the problem of predicting gender from still images using human metrology. Since the values of the anthropometric measurements are difficult to be estimated accurately from state-of-the-art computer vision algorithms, ratios of anthropometric measurements were used as features. Additionally, since several measurements will not be available at test time in a real-life scenario, we opted for the Learning Using Privileged Information (LUPI) paradigm. During training, we used as features, ratios from all the available anthropometric measurements, whereas at test time only ratios of measurable (i.e., observable) quantities were used. We show that by using the LUPI framework, the estimation of soft biometric characteristics such as gender is possible. Gender classification from human metrology is also tested on real images with promising results.
KW - Anthropometry
KW - Gender Classification
KW - Privileged Information
KW - Soft Biometrics
UR - http://www.scopus.com/inward/record.url?scp=85006802570&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006802570&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2016.7532941
DO - 10.1109/ICIP.2016.7532941
M3 - Conference contribution
AN - SCOPUS:85006802570
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 3156
EP - 3160
BT - 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 25 September 2016 through 28 September 2016
ER -