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A Data Annotation Process for Human Activity Recognition in Public Places

Cormier, Mickael

Abstract (englisch):

Behavior analysis of individuals in crowds or groups of people in public
places through surveillance cameras gains importance for several different actors. Automatically detecting and understanding pedestrians in real-world uncooperative scenarios is very challenging. Common issues such as limited annotated data, unreliable data and annotation quality, and appropriate use of this data for supervised learning often originate in steps preceding the modeling of specialized neural network architectures. In this report, the necessity and requirements for designing a reliable data annotation process are presented. Some precise ideas for automation through neural networks are discussed in a conceptual manner.

Verlagsausgabe §
DOI: 10.5445/IR/1000135073
Veröffentlicht am 06.07.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2021
Sprache Englisch
Identifikator ISBN: 978-3-7315-1091-8
KITopen-ID: 1000135073
Erschienen in Proceedings of the 2020 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. Ed.: J. Beyerer; T. Zander
Verlag KIT Scientific Publishing
Seiten 33-51
Serie Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe ; 51
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