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Focus-of-attention for human activity recognition from UAVs

Author: Burghouts, G.J. · Eekeren, A.W.M. van · Dijk, J.
Type:article
Date:2014
Publisher: SPIE
Source:Huckridge D.A.Ebert R., Proceedings of SPIE - The International Society for Optical Engineering, 9249
Identifier: 523241
Article number: 92490T
Keywords: Airborne platforms · Human activity recognition · Human detection · Motion-in-motion · Pattern recognition · Tracking · Aircraft detection · Graphical user interfaces · Infrared devices · Surface discharges · User interfaces · Focus of Attention · Full motion video · Human activities · Motion features

Abstract

This paper presents a system to extract metadata about human activities from full-motion video recorded from a UAV. The pipeline consists of these components: tracking, motion features, representation of the tracks in terms of their motion features, and classification of each track as one of the human activities of interest. We consider these activities: walk, run, throw, dig, wave. Our contribution is that we show how a robust system can be constructed for human activity recognition from UAVs, and that focus-of-attention is needed. We find that tracking and human detection are essential for robust human activity recognition from UAVs. Without tracking, the human activity recognition deteriorates. The combination of tracking and human detection is needed to focus the attention on the relevant tracks. The best performing system includes tracking, human detection and a per-track analysis of the five human activities. This system achieves an average accuracy of 93%. A graphical user interface is proposed to aid the operator or analyst during the task of retrieving the relevant parts of video that contain particular human activities. Our demo is available on YouTube.