MMU GASPFA: A COTS multimodal biometric database

This paper describes the baseline corpus of a new multimodal biometric database, the MMU GASPFA (Gait–Speech–Face) database. The corpus in GASPFA is acquired using commercial off the shelf (COTS) equipment including digital video cameras, digital voice recorder, digital camera, Kinect camera and accelerometer equipped smart phones. The corpus consists of frontal face images from the digital camera, speech utterances recorded using the digital voice recorder, gait videos with their associated data recorded using both the digital video cameras and Kinect camera simultaneously as well as accelerometer readings from the smart phones. A total of 82 participants had their biometric data recorded. MMU GASPFA is able to support both multimodal biometric authentication as well as gait action recognition. This paper describes the acquisition setup and protocols used in MMU GASPFA, as well as the content of the corpus. Baseline results from a subset of the participants are presented for validation purposes.

► The MMU GASPFA database contains audio, video and accelerometer data for 82 subjects.
► Data were recorded using commercial off the shelf sensors in a real live setting.
► Gait data were recorded using both digital video and video with depth and accelerometers.
► Gait data were recorded under 11 conditions, including novel usage of traditional clothing.
► Gait action such as standstill, normal walk, brisk walk and encumbered walk are recorded.