FLIC

We collected a 5003 image dataset automatically 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 groundtruthlabeling. Each image was annotated by five Turkers for $0.01 each to label 10 upperbody joints. The median-of-five labeling was taken in each image to be robust to outlier annotation. Finally, images were rejected manually by us if the person was occluded or severely non-frontal. We set aside 20% (1016 images) of the data for testing.

搜集汇总

背景与挑战

背景概述

FLIC数据集是一个包含5003张从好莱坞电影中提取的图像数据集，用于人物姿态评估，标注了10个上半身关节，其中20%的图像用于测试。