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Image-based camera localization: an overview.

Yihong Wu1, Fulin Tang2, Heping Li2

  • 1National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China, University of Chinese Academy of Sciences, Beijing, China. yhwu@nlpr.ia.ac.cn.

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Summary
This summary is machine-generated.

This review provides a comprehensive overview of image-based camera localization, a critical task for virtual reality, robotics, and autonomous driving. It offers a new classification of methods and discusses future trends for researchers and engineers.

Keywords:
Camera localizationCamera pose determinationPnP problemSLAM

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Area of Science:

  • Computer Vision
  • Robotics
  • Artificial Intelligence

Background:

  • Image-based camera localization is crucial for emerging technologies like virtual reality, augmented reality, robotics, and autonomous driving.
  • Existing literature lacks a complete review, hindering rapid entry into this field for new researchers and engineers.

Purpose of the Study:

  • To provide a comprehensive overview and classification of image-based camera localization approaches.
  • To introduce related techniques and discuss future development trends in the field.

Main Methods:

  • Systematic review and classification of existing image-based camera localization techniques.
  • Introduction and explanation of various related methodologies.
  • Analysis of current trends and future research directions.

Main Results:

  • A novel and complete classification of image-based camera localization approaches is presented.
  • Key techniques within each category are introduced and explained.
  • Identified trends and potential future research avenues are discussed.

Conclusions:

  • This paper serves as a valuable resource for understanding the landscape of image-based camera localization.
  • It aims to facilitate quicker adoption and advancement in the field for both academic and industrial communities.