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Dynamic Environment Sensing Using an Intelligent Vehicle

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Abbreviations

Classification:

Annotating a data segment or an object by a class label.

Contextual map:

A map containing high-level knowledge beyond geometry, such as object, class, and motion.

Data alignment:

Integrating the instantaneous measurements from sensors’ coordinate system(s) to a global coordinate system.

Dynamic mapping:

A mapping technology that uses a dynamic procedure or generates a map of a dynamic environment.

Multi-laser sensing system:

A sensor system that makes collaborative use of a number of laser range scanners.

Range image:

A 2D image where the value of each pixel is a range distance, with the pixel index corresponding to range angle and scanning sequence, so that a 3D coordinate can be retrieved for each pixel of the range image.

Scene understanding:

Converting from low-level knowledge to high-level knowledge of an environment.

Segmentation:

Making partitions on a data set, where in each partition cell (i.e., segment), data has the property of certain homogeneity.

Sensor calibration:

Finding a set of parameters that describes internal or external sensor geometry.

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Author information

Authors and Affiliations

  1. Key Lab of Machine Perception (MOE), Peking University, Beijing, 100871, China

    Dr. Huijing Zhao, Long Xiong, Yiming Liu, Xiaolong Zhu, Yipu Zhao & Hongbin Zha

Authors
  1. Dr. Huijing Zhao
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  2. Long Xiong
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  3. Yiming Liu
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  4. Xiaolong Zhu
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  5. Yipu Zhao
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  6. Hongbin Zha
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Editor information

Editors and Affiliations

  1. Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX, USA

    Mehrdad Ehsani

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Fei-Yue Wang

  3. Center for Urban Transportation Research, University of South Florida, Tampa, FL, USA

    Gary L. Brosch

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Zhao, H., Xiong, L., Liu, Y., Zhu, X., Zhao, Y., Zha, H. (2013). Dynamic Environment Sensing Using an Intelligent Vehicle . In: Ehsani, M., Wang, FY., Brosch, G.L. (eds) Transportation Technologies for Sustainability. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5844-9_482

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