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Effective Self Attention Modeling for Aspect Based Sentiment Analysis Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Application of Hierarchical Clustering for Object Tracking with a Dynamic Vision Sensor

Authors : Tobias Bolten, Regina Pohle-Fröhlich, Klaus D. Tönnies

Published in: Computational Science – ICCS 2019

Publisher: Springer International Publishing

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Abstract

Monitoring public space with imaging sensors to perform an object- or person-tracking is often associated with privacy concerns. We present a Dynamic Vision Sensor (DVS) based approach to achieve this tracking that does not require the creation of conventional grey- or color images. These Dynamic Vision Sensors produce an event-stream of information, which only includes the changes in the scene.
The presented approach for tracking considers the scenario of fixed mounted sensors. The method is based on clustering events and tracing the resulting cluster centers to accomplish the object tracking. We show the usability of this approach with a first proof-of-concept test.

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Footnotes
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Metadata
Title
Application of Hierarchical Clustering for Object Tracking with a Dynamic Vision Sensor
Authors
Tobias Bolten
Regina Pohle-Fröhlich
Klaus D. Tönnies
Copyright Year
2019
Book
Computational Science – ICCS 2019

Print ISBN: 978-3-030-22749-4

Electronic ISBN: 978-3-030-22750-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-22750-0_13

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