  A video dataset that is designed to study fine-grained categorisation of
pedestrians is introduced. Pedestrians were recorded "in-the-wild" from a
moving vehicle. Annotations include bounding boxes, tracks, 14 keypoints with
occlusion information and the fine-grained categories of age (5 classes), sex
(2 classes), weight (3 classes) and clothing style (4 classes). There are a
total of 27,454 bounding box and pose labels across 4222 tracks. This dataset
is designed to train and test algorithms for fine-grained categorisation of
people, it is also useful for benchmarking tracking, detection and pose
estimation of pedestrians. State-of-the-art algorithms for fine-grained
classification and pose estimation were tested using the dataset and the
results are reported as a useful performance baseline.
