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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

Scene Parsing and Fusion-Based Continuous Traversable Region Formation

verfasst von : Xuhong Xiao, Gee Wah Ng, Yuan Sin Tan, Yeo Ye Chuan

Erschienen in: Computer Vision - ACCV 2014 Workshops

Verlag: Springer International Publishing

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Abstract

Determining the categories of different parts of a scene and generating a continuous traversable region map in the physical coordinate system are crucial for autonomous vehicle navigation. This paper presents our efforts in these two aspects for an autonomous vehicle operating in open terrain environment. Driven by the ideas that have been proposed in our Cognitive Architecture, we have designed novel strategies for the top-down facilitation process to explicitly interpret spatial relationship between objects in the scene, and have incorporated a visual attention mechanism into the image-based scene parsing module. The scene parsing module is able to process images fast enough for real-time vehicle navigation applications. To alleviate the challenges in using sparse 3D occupancy grids for path planning, we are proposing an approach to interpolate the category of occupancy grids not hit by 3D LIDAR, with reference to the aligned image-based scene parsing result, so that a continuous \(2\frac{1}{2}D\) traversable region map can be formed.

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Metadaten
Titel
Scene Parsing and Fusion-Based Continuous Traversable Region Formation
verfasst von
Xuhong Xiao
Gee Wah Ng
Yuan Sin Tan
Yeo Ye Chuan
Copyright-Jahr
2015
Buch
Computer Vision - ACCV 2014 Workshops

Print ISBN: 978-3-319-16627-8

Electronic ISBN: 978-3-319-16628-5

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-16628-5_28

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