Pilot study on real-time motion detection in UAS video data by human observer and image exploitation algorithm

Jutta Hild; Wolfgang Krüger; Stefan Brüstle; Patrick Trantelle; Gabriel Unmüßig; Michael Voit; Norbert Heinze; Elisabeth Peinsipp-Byma; Jürgen Beyerer

doi:10.1117/12.2262477

1 May 2017 Pilot study on real-time motion detection in UAS video data by human observer and image exploitation algorithm

Jutta Hild, Wolfgang Krüger, Stefan Brüstle, Patrick Trantelle, Gabriel Unmüßig, Michael Voit, Norbert Heinze, Elisabeth Peinsipp-Byma, Jürgen Beyerer

Author Affiliations +

Proceedings Volume 10199, Geospatial Informatics, Fusion, and Motion Video Analytics VII; 1019903 (2017) https://doi.org/10.1117/12.2262477
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

Real-time motion video analysis is a challenging and exhausting task for the human observer, particularly in safety and security critical domains. Hence, customized video analysis systems providing functions for the analysis of subtasks like motion detection or target tracking are welcome. While such automated algorithms relieve the human operators from performing basic subtasks, they impose additional interaction duties on them. Prior work shows that, e.g., for interaction with target tracking algorithms, a gaze-enhanced user interface is beneficial. In this contribution, we present an investigation on interaction with an independent motion detection (IDM) algorithm. Besides identifying an appropriate interaction technique for the user interface – again, we compare gaze-based and traditional mouse-based interaction – we focus on the benefit an IDM algorithm might provide for an UAS video analyst. In a pilot study, we exposed ten subjects to the task of moving target detection in UAS video data twice, once performing with automatic support, once performing without it. We compare the two conditions considering performance in terms of effectiveness (correct target selections). Additionally, we report perceived workload (measured using the NASA-TLX questionnaire) and user satisfaction (measured using the ISO 9241-411 questionnaire). The results show that a combination of gaze input and automated IDM algorithm provides valuable support for the human observer, increasing the number of correct target selections up to 62% and reducing workload at the same time.

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Jutta Hild, Wolfgang Krüger, Stefan Brüstle, Patrick Trantelle, Gabriel Unmüßig, Michael Voit, Norbert Heinze, Elisabeth Peinsipp-Byma, and Jürgen Beyerer "Pilot study on real-time motion detection in UAS video data by human observer and image exploitation algorithm", Proc. SPIE 10199, Geospatial Informatics, Fusion, and Motion Video Analytics VII, 1019903 (1 May 2017); https://doi.org/10.1117/12.2262477

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KEYWORDS

Video

Detection and tracking algorithms

Video surveillance

Motion detection

Motion analysis

Visualization

Human-machine interfaces

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