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  • 8 - Perception and computer vision

  • Edited by Keith Frankish, The Open University, Milton Keynes, William M. Ramsey, University of Nevada, Las Vegas
  • Book:
    The Cambridge Handbook of Artificial Intelligence
    Published online:
    05 July 2014
    Print publication:
    12 June 2014, pp 168-190

  • Summary

    This chapter focuses on visual perception, which is the dominant sense in humans and has been used from the first days of building artificial machines. It highlights the state of the art in computer vision methods that have been found to operate well and that led to the development of capabilities. The chapter summarizes the work structured into four key topics: object recognition and categorization, tracking and visual servoing, understanding human behavior, and contextual scene understanding. Scene geometry is an important intermediate representation in the interpretation process of an image. Object recognition can be seen as the challenge to determine the where and what of objects in a scene. Surveillance systems often work in two phases: a learning phase and a run-time phase. The chapter concludes with a critical assessment of what computer vision has achieved and what challenges remain.