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2016 | OriginalPaper | Buchkapitel

Learning Social Etiquette: Human Trajectory Understanding In Crowded Scenes

verfasst von : Alexandre Robicquet, Amir Sadeghian, Alexandre Alahi, Silvio Savarese

Erschienen in: Computer Vision – ECCV 2016

Verlag: Springer International Publishing

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Abstract

Humans navigate crowded spaces such as a university campus by following common sense rules based on social etiquette. In this paper, we argue that in order to enable the design of new target tracking or trajectory forecasting methods that can take full advantage of these rules, we need to have access to better data in the first place. To that end, we contribute a new large-scale dataset that collects videos of various types of targets (not just pedestrians, but also bikers, skateboarders, cars, buses, golf carts) that navigate in a real world outdoor environment such as a university campus. Moreover, we introduce a new characterization that describes the “social sensitivity” at which two targets interact. We use this characterization to define “navigation styles” and improve both forecasting models and state-of-the-art multi-target tracking–whereby the learnt forecasting models help the data association step.

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Vorheriges Kapitel Accelerating Convolutional Neural Networks with Dominant Convolutional Kernel and Knowledge Pre-regression

Nächstes Kapitel Bayesian Image Based 3D Pose Estimation

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Titel: Learning Social Etiquette: Human Trajectory Understanding In Crowded Scenes
verfasst von: Alexandre Robicquet
Amir Sadeghian
Alexandre Alahi
Silvio Savarese
Verlag: Springer International Publishing
Buch: Computer Vision – ECCV 2016
Print ISBN: 978-3-319-46483-1

Electronic ISBN: 978-3-319-46484-8

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-46484-8_33

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