TY - GEN
T1 - Accio
T2 - 5th ACM International Conference on Multimedia Retrieval, ICMR 2015
AU - Ghaleb, Esam
AU - Tapaswi, Makarand
AU - Al-Halah, Ziad
AU - Ekenel, Hazim Kemal
AU - Stiefelhagen, Rainer
PY - 2015/6/22
Y1 - 2015/6/22
N2 - Video face recognition is a very popular task and has come a long way. The primary challenges such as illumination, resolution and pose are well studied through multiple data sets. However there are no video-based data sets dedicated to study the effects of aging on facial appearance. We present a challenging face track data set, Harry Potter Movies Aging Data set (Accio1), to study and develop age invariant face recognition methods for videos. Our data set not only has strong challenges of pose, illumination and distractors, but also spans a period of ten years providing substantial variation in facial appearance. We propose two primary tasks: within and across movie face track retrieval; and two protocols which differ in their freedom to use external data. We present baseline results for the retrieval performance using a state-of-the-art face track descriptor. Our experiments show clear trends of reduction in performance as the age gap between the query and database increases. We will make the data set publicly available for further exploration in ageinvariant video face recognition.
AB - Video face recognition is a very popular task and has come a long way. The primary challenges such as illumination, resolution and pose are well studied through multiple data sets. However there are no video-based data sets dedicated to study the effects of aging on facial appearance. We present a challenging face track data set, Harry Potter Movies Aging Data set (Accio1), to study and develop age invariant face recognition methods for videos. Our data set not only has strong challenges of pose, illumination and distractors, but also spans a period of ten years providing substantial variation in facial appearance. We propose two primary tasks: within and across movie face track retrieval; and two protocols which differ in their freedom to use external data. We present baseline results for the retrieval performance using a state-of-the-art face track descriptor. Our experiments show clear trends of reduction in performance as the age gap between the query and database increases. We will make the data set publicly available for further exploration in ageinvariant video face recognition.
UR - https://www.scopus.com/pages/publications/84962440832
U2 - 10.1145/2671188.2749296
DO - 10.1145/2671188.2749296
M3 - Conference contribution
AN - SCOPUS:84962440832
T3 - ICMR 2015 - Proceedings of the 2015 ACM International Conference on Multimedia Retrieval
SP - 455
EP - 458
BT - ICMR 2015 - Proceedings of the 2015 ACM International Conference on Multimedia Retrieval
PB - Association for Computing Machinery
Y2 - 23 June 2015 through 26 June 2015
ER -