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D4FLY multimodal biometric database: multimodal fusion evaluation envisaging on-the-move biometric-based border control
This work presents a novel multimodal biometric
dataset with emerging biometric traits including 3D face,
thermal face, iris on-the-move, iris mobile, somatotype and
smartphone sensors. This dataset was created to resemble
on-the-move characteristics in applications such as border
control. The five types of biometric traits were selected as
they can be captured while on-the-move, are contactless,
and show potential for use in a multimodal fusion verification system in a border control scenario. Innovative sensor hardware was used in the data capture. The data featuring these biometric traits will be a valuable contribution to advancing biometric fusion research in general. Baseline evaluation was performed on each unimodal dataset. Multimodal fusion was evaluated based on various scenarios for comparison. Real-time performance is presented based on an Automated Border Control (ABC) scenario