Geometric constraints for human detection in aerial imagery

Vladimir Reilly, Berkan Solmaz, Mubarak Shah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations


In this paper, we propose a method for detecting humans in imagery taken from a UAV. This is a challenging problem due to small number of pixels on target, which makes it more difficult to distinguish people from background clutter, and results in much larger searchspace. We propose a method for human detection based on a number of geometric constraints obtained from the metadata. Specifically, we obtain the orientation of groundplane normal, the orientation of shadows cast by humans in the scene, and the relationship between human heights and the size of their corresponding shadows. In cases when metadata is not available we propose a method for automatically estimating shadow orientation from image data. We utilize the above information in a geometry based shadow, and human blob detector, which provides an initial estimation for locations of humans in the scene. These candidate locations are then classified as either human or clutter using a combination of wavelet features, and a Support Vector Machine. Our method works on a single frame, and unlike motion detection based methods, it bypasses the global motion compensation process, and allows for detection of stationary and slow moving humans, while avoiding the search across the entire image, which makes it more accurate and very fast. We show impressive results on sequences from the VIVID dataset and our own data, and provide comparative analysis.

Original languageEnglish (US)
Title of host publicationComputer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings
PublisherSpringer Verlag
Number of pages14
EditionPART 6
ISBN (Print)3642155669, 9783642155666
StatePublished - 2010
Externally publishedYes
Event11th European Conference on Computer Vision, ECCV 2010 - Heraklion, Crete, Greece
Duration: Sep 10 2010Sep 11 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 6
Volume6316 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th European Conference on Computer Vision, ECCV 2010
CityHeraklion, Crete

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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