Human Identity Recognition in Aerial Images

Human identity recognition is an important yet underaddressed problem. Previous methods were strictly limited to high quality photographs, where the principal techniques heavily rely on body details such as face detection. In this paper, we propose an algorithm to address the novel problem of human identity recognition over a set of unordered low quality aerial images. Assuming a user was able to manually locate a target in some images of the set, we find the target in each other query image by implementing a weighted voter-candidate formulation. In the framework, every manually located target is a voter, and the set of humans in a query image are candidates. In order to locate the target, we detect and align blobs of voters and candidates. Consequently, we use PageRank to extract distinguishing regions, and then match multiple regions of a voter to multiple regions of a candidate using Earth Mover Distance (EMD). This generates a robust similarity measure between ever...

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Omar Oreifej, Ramin Mehran, and Mubarak Shah
• Keywords: CVPR 2010, Human Detection, Object Identification, Object Matching