Accio: A data set for face track retrieval in movies across age

Esam Ghaleb*, Makarand Tapaswi, Ziad Al-Halah, Hazim Kemal Ekenel, Rainer Stiefelhagen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review


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 (Accio 1), 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 …
Original languageEnglish
Title of host publicationProceedings of the 5th ACM on International Conference on Multimedia Retrieval (ICMR '15)
Publication statusPublished - 22 Jun 2015
Externally publishedYes

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