Where’s Waldo: Matching People in Images of Crowds
Given a community-contributed set of photos of a crowded public event, this paper addresses the problem of ﬁnding all images of each person in the scene. This problem is very challenging due to large changes in camera viewpoints, severe occlusions, low resolution and photos from tens or hundreds of different photographers. Despite these challenges, the problem is made tractable by exploiting a variety of visual and contextual cues – appearance, timestamps, camera pose and co-occurrence of people. This paper demonstrates an approach that integrates these cues to enable high quality person matching in community photo collections downloaded from Flickr.com
Citation: “Where’s Waldo: Matching People in Images of Crowds”, Rahul Garg, Deva Ramanan, Steven M. Seitz, Noah Snavely, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 2011, pp. 1793-1800.
And here’s a PDF of the paper itself. I’d love to see the Google Analytics results for this paper: Iran, China, Burma, Occupy Wall St…