The FLIC dataset contains 5003 images from popular Hollywood movies. The images were obtained by running a state-of-the-art person detector on every tenth frame of 30 movies. People detected with high confidence (roughly 20K candidates) were then sent to the crowdsourcing marketplace Amazon Mechanical Turk to obtain ground truth labelling. Each image was annotated by five Turkers to label 10 upper body joints. The median-of-five labelling was taken in each image to be robust to outlier annotation. Finally, images were rejected manually by if the person was occluded or severely non-frontal.