7. Applications in Computer Vision, Image Retrieval and Robotics

  1. Liming Zhang1 and
  2. Weisi Lin2

Published Online: 20 MAR 2013

DOI: 10.1002/9780470828144.ch7

Selective Visual Attention: Computational Models and Applications

Selective Visual Attention: Computational Models and Applications

How to Cite

Zhang, L. and Lin, W. (2013) Applications in Computer Vision, Image Retrieval and Robotics, in Selective Visual Attention: Computational Models and Applications, John Wiley & Sons (Asia) Pte Ltd, Singapore. doi: 10.1002/9780470828144.ch7

Author Information

  1. 1

    Fudan University, P. R. China

  2. 2

    Nanyang Technological University, Singapore

Publication History

  1. Published Online: 20 MAR 2013
  2. Published Print: 27 MAR 2013

ISBN Information

Print ISBN: 9780470828120

Online ISBN: 9780470828144

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Keywords:

  • object detection;
  • object recognition;
  • computer vision;
  • scale invariant feature transform (SIFT);
  • speeded up robust feature (SURF);
  • support vector machine(SVM);
  • seed region growing;
  • frequency tuned saliency (FTS);
  • histogram-based contrast;
  • condition random field (CRF);
  • HMAX network;
  • satellite imagery;
  • phase biquaternion Fourier transform (PBFT);
  • Hough transform;
  • gist feature;
  • image retrieval;
  • simultaneous localization and mapping (SLAM);
  • gaze control;
  • optical flow field

Summary

In this chapter, we begin to switch our focus from the visual attention modelling of Chapters 3–6 to the applications of these models. In Chapter 7, we first introduce the conventional engineering methods for object detection and recognition in Section 7.1. Then attention modelling combined with object detection and recognition for natural scenes is presented in Section 7.2. Since satellite images are different from natural images, in Section 7.3 we introduce the attention assisted object detection and recognition for satellite images. Section 7.4 presents image retrieval via visual attention. Another application of visual attention is presented finally for robots.

This chapter does not try to introduce all aspects and works related to computer vision, image retrieval and robotics based on visual attention, but only demonstrates some typical methods of combining visual attention with conventional engineering methods. Readers can infer other aspects from these introduced applications.