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2016 | OriginalPaper | Buchkapitel

A Direct Method for Robust Model-Based 3D Object Tracking from a Monocular RGB Image

verfasst von : Byung-Kuk Seo, Harald Wuest

Erschienen in: Computer Vision – ECCV 2016 Workshops

Verlag: Springer International Publishing

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Abstract

This paper proposes a novel method for robust 3D object tracking from a monocular RGB image when an object model is available. The proposed method is based on direct image alignment between consecutive frames over a 3D target object. Unlike conventional direct methods that only rely on image intensity, we newly model intensity variations using the surface normal of the object under the Lambertian assumption. From the prediction about image intensity in this model, we also employ a constrained objective function, which significantly alleviates degradation of the tracking performance. In experiments, we evaluate our method using datasets that consist of test sequences under challenging conditions, and demonstrate its benefits compared to other methods.

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Vorheriges Kapitel Visual Analogies: A Framework for Defining Aspect Categorization

Nächstes Kapitel A Radial Search Method for Fast Nearest Neighbor Search on Range Images

In model-based approaches, simultaneous localization and mapping-based methods can be considered for pose estimation in unknown 3D environments, but they are not suitable for 3D object tracking that aims at estimating poses relative to target objects; thus, we do not detail methods in this category.

Since the relation of the \(\mathcal {G}\) to the camera pose is straightforward, this paper retains the same notation \(\varvec{\xi }\) for the camera pose or motion.

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Titel: A Direct Method for Robust Model-Based 3D Object Tracking from a Monocular RGB Image
verfasst von: Byung-Kuk Seo
Harald Wuest
Verlag: Springer International Publishing
Buch: Computer Vision – ECCV 2016 Workshops
Print ISBN: 978-3-319-49408-1

Electronic ISBN: 978-3-319-49409-8

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-49409-8_48

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