Fig. 1: Human data extraction in computer-vision papers and downstream patents.
From: Computer-vision research powers surveillance technology
a, Relative frequencies of data types extracted from computer-vision papers and patents. For each year from 2010 to 2019, we randomly sampled and analysed ten paper–patent pairs (n = 200). Most of the annotated computer-vision papers and patents (88%, s.d. = 5.7%) refer to data about humans. Most of the papers and patents (68%, s.d. = 4.7%) specifically refer to data about human bodies and body parts. Only 1% (s.d. = 0.7%) of the papers and patents targeted exclusively non-socially salient data. b, Examples of images analysed in computer-vision papers. For a random sample of the computer-vision papers (n = 50), we display one example of an image analysed by the paper. For papers that analysed any images containing humans, we display an example of these images of humans (highlighted in red). For papers that did not analyse any images of humans, we display an example of these non-human-depicting images (highlighted in grey). Many papers analysed images of humans. Images in b are adapted from the following references and are, unless otherwise stated, from IEEE, under a Creative Commons licence CC BY ND. Top row, left to right: refs. 51,52,53,54,55,56,57,58,59,60. Second row, left to right: refs. 61,62,63,64,65,66,67,68,69,70. Third row, left to right: refs. 71,72,73,74,75,76,77,78,79,80. Fourth row, left to right (except second image): refs. 81,82,83,84,85,86,87,88,89. Fifth row, left to right: refs. 90,91,92,93,94,95,96,97,98,99. Fourth row (second image): ref. 100, arXiv, under a non-exclusive licence to distribute.
