Many of the existing gait datasets are limited by their lack of diversity in terms of the participants (e.g., gender, age, height, weight, ethnicity), recording environments (e.g., recording angles, indoors / outdoors), and availability. Therefore, we present a gait dataset containing 65 diverse participants with both indoor and outdoor environments. The data was acquired using 2 digital cameras and a digital goniometer (used to measure joint angles). Each participant provided 24 walking sequences from a range of viewing angles (360 degrees in 45 degree increments). Each participant also provided an alternative outfit to provide diversity in personal appearance. 

This dataset will be of value to applications gait identification, human pose estimation, and more.