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TREAT: Terse Rapid Edge-Anchored Tracklets

Trichet, Remi and O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 (2016) TREAT: Terse Rapid Edge-Anchored Tracklets. In: 4th Workshop on Activity Monitoring by Multiple Distributed Sensing, 23 Aug 2016, Colorado Springs, CO.. ISBN 978-1-5090-3811-4

Abstract
Fast computation, efficient memory storage, and performance on par with standard state-of-the-art descriptors make binary descriptors a convenient tool for many computer vision applications. However their development is mostly tailored for static images. To respond to this limitation, we introduce TREAT (Terse Rapid Edge-Anchored Tracklets), a new binary detector and descriptor, based on tracklets. It harnesses moving edge maps to perform efficient feature detection, tracking, and description at low computational cost. Experimental results on 3 different public datasets demonstrate improved performance over other popular binary features. These experiments also provide a basis for benchmarking the performance of binary descriptors in video-based applications.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: Proceedings of IEEE AVSS 2016. . IEEE. ISBN 978-1-5090-3811-4
Publisher:IEEE
Copyright Information:© 2016 IEEE
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:21327
Deposited On:23 Aug 2016 09:56 by Noel Edward O'connor . Last Modified 19 Oct 2018 09:26
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