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7 Attentive Classification

  • Simone Frintrop
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3899)

Abstract

According to [Neisser, 1967], object recognition in human perception is done in two steps: first, attentional processes select a region of interest, and second, complex object recognition is restricted to these regions. In the previous chapters, we introduced the computational attention system VOCUS that performs the first of these steps. In this chapter, we realize the second step: VOCUS is combined with a well-known classifier [Viola and Jones, 2004] resulting in a complete recognition system. This approach is called attentive classification (cf. Fig. 7.1).

Keywords

Object Recognition Training Image False Detection Salient Object Attention System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Simone Frintrop

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