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Advanced Technologies in Modern Robotic Applications pp 97–156Cite as

Object Detection and Tracking

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Abstract

Visual sensors provide comprehensive and abundant information of surrounding environment. In this chapter, we will first give a brief introduction of visual recognition with basic concepts and algorithms, followed by the introduction of the useful software toolkit JavaScript Object Notation (JSON) framework. Then we will review a series of vision-based object recognition and tracking techniques. The detection and classification of pedestrians in infrared thermal images is investigated using deep learning method. And the algorithm for tracking single moving objects based on JSON visual recognition framework is also introduced. As the extension of single moving objects tracking, we will also show the visual tracking to multiple moving objects with the aid of the particle swarm optimization (PSO) method.

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Author information

Authors and Affiliations

  1. Key Lab of Autonomous Systems and Networked Control, Ministry of Education, South China University of Technology, Guangzhou, China

    Chenguang Yang

  2. Centre for Robotics and Neural Systems, Plymouth University, Devon, UK

    Chenguang Yang

  3. School of Automation, Beijing Institute of Technology, Beijing, China

    Hongbin Ma & Mengyin Fu

  4. State Key Lab of Intelligent Control and Decision of Complex System, Beijing Institute of Technology, Beijing, China

    Hongbin Ma & Mengyin Fu

Authors
  1. Chenguang Yang
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  2. Hongbin Ma
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  3. Mengyin Fu
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Correspondence to Chenguang Yang or Hongbin Ma .

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© 2016 Science Press and Springer Science+Business Media Singapore

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Yang, C., Ma, H., Fu, M. (2016). Object Detection and Tracking. In: Advanced Technologies in Modern Robotic Applications. Springer, Singapore. https://doi.org/10.1007/978-981-10-0830-6_4

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  • DOI: https://doi.org/10.1007/978-981-10-0830-6_4

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  • Print ISBN: 978-981-10-0829-0

  • Online ISBN: 978-981-10-0830-6

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