Title

Human Identity Recognition In Aerial Images

Abstract

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 every voter-candidate pair. Finally, we identify the candidate with the highest weighted vote as the target. We tested our technique over several aerial image sets that we collected, along with publicly available sets, and have obtained promising results. ©2010 IEEE.

Publication Date

8-31-2010

Publication Title

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Number of Pages

709-716

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/CVPR.2010.5540147

Socpus ID

77955988233 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/77955988233

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