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  4. A Data Annotation Process for Human Activity Recognition in Public Places
 
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2021
Conference Paper
Title

A Data Annotation Process for Human Activity Recognition in Public Places

Abstract
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.
Author(s)
Cormier, Mickael  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Mainwork
Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory 2020. Proceedings  
Conference
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation and Institute for Anthropomatics, Vision and Fusion Laboratory (Joint Workshop) 2020  
Open Access
DOI
10.24406/publica-r-411593
10.5445/IR/1000135073
File(s)
N-638372.pdf (5.13 MB)
Rights
CC BY 4.0: Creative Commons Attribution
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
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