AIM (Age Induced Makeup)

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Dataset Description:

The Age Induced Makeup (AIM) dataset consists of presentation attacks in the form of age progressive makeups. The identities comprise of male and female subjects from various ethnicities. Professional artists have created varying degrees of facial makeups to generate an old-age appearance. The dataset has been created for experiments related to detection of makeup-based presentation attacks on face recognition systems.

Samples of age-induced makeup with different levels of makeup intensity from AIM dataset. For each row, the left image is bona-fide, and intensity of makeup increases from left to right.

If you use this dataset, please cite the following publication:

@article{Kotwal_TBIOM_2019,
	author = {Kotwal, Ketan and Mostaani, Zohreh and Marcel, S\'{e}bastien},
	title = {Detection of Age-Induced Makeup Attacks on Face Recognition Systems Using Multi-Layer Deep Features},
	journal = {IEEE Transactions on Biometrics, Behavior, and Identity Science},
	publisher = {{IEEE}},
	year = {2019},
}

Data Collection:

The AIM dataset consists of 456 video recordings from both bona fide and presentation attack (PA) videos (each ≈ 10 s in duration). These videos have been acquired in using the RGB channel of Intel RealSense SR300 camera.

The dataset consists of 240 bona fide (non-makeup) presentations corresponding to 72 subjects; and 216 attack (age induced makeup) presentations captured from a subset of 20 subjects. For every participant of makeup presentation of AIM, a bona fide (non-makeup) video is also available.

Makeups were created by professionals using regular makeup materials to compose age-inducing effects like coloring of eyebrows, and creation of wrinkles on cheeks, or forehead. No prosthetic objects or materials were considered.

The AIM dataset is a subset of WMCA dataset collected at Idiap Research Institute. For details on WMCA dataset, please refer: https://www.idiap.ch/dataset/wmca

A complete preprocessed data for the aforementioned videos have been provided to facilitate reproducing experiments from the reference publication, as well as to conduct new experiments. The details of preprocessing can be found in the reference publication.

The implementation of all experiments described in the reference publication is available at https://gitlab.idiap.ch/bob/bob.paper.makeup_aim

Experimental Protocol:

The reference publication considers the experimental protocol named grandtest. For a frame-level evaluation, 20 frames from each video have been used. For the grandtest protocol, videos were divided into fixed, disjoint groups: train, dev, and eval. Each group consists of unique subset of subjects. (Subjects of one group are not present in other two).

Details of the grandtest protocol are summarized below: