Detecting humans from a top-down perspective using an unmanned aerial vehicle

Stokkel, X.L.X. (2015) Detecting humans from a top-down perspective using an unmanned aerial vehicle. Bachelor's Thesis, Artificial Intelligence.

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Abstract

Search and rescue is often time and labour intensive, large groups of people search vast areas for missing people. In this paper we present a system that uses a drone to make search and rescue less resource intensive. The system uses a downward facing camera on the drone to detect people in open areas. The detector uses a sliding window to extract histogram of oriented gradients features that are classified using a Linear Support Vector Machine. Several preprocessing methods and models are compared for their classification and runtime performance. We also introduce a method to dynamically determine whether positive windows are true positives by looking at how they overlap. By doing this we hope to bring down the amount of false positives when the detector is used to count the number of people in an image. Our experiments show that the developed method has good performance on classifying frames as containing persons, and is able to estimate the number of people on a frame with a mean squared error of less than 0.25. Although the detector shows great promise the current implementation is too slow to be of practical use.

Item Type:	Thesis (Bachelor's Thesis)
Supervisor name:	Wiering, M.A. and Martings, F.N.
Degree programme:	Artificial Intelligence
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	15 Feb 2018 08:05
Last Modified:	02 May 2019 11:18
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/13020

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