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A Survey of Visual Perception Approaches

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Human Centred Intelligent Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 189))

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Abstract

The capacity to recognize perceptual organizations is a conventional human ability that demonstrates a peerless challenge for researchers of computer science.  Compared to object recognition and image segmentation, which are considered as the primary interests of the image processing research, visual perception has fewer generic solutions or evaluated approaches. In this paper, we explain the difficulty of the visual perception process and we offer a structured survey of the related approaches. We focus on each approach, along with its advantages and disadvantages. Then we present a comparison and an evaluation of different approaches based on a number of chosen criteria. Finally, we propose an approach to model the visual perception using stochastic geometry. To solve the problem of pixel-based approach and to inject high-level knowledge, we propose a marked point process model.

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Authors and Affiliations

  1. Faculty of Sciences of Tunis, University of Tunis EL MANAR, B.P. No. 94 - Rommana, 1068, Tunis, Tunisia

    Amal Mbarki & Mohamed Naouai

  2. Computer Science Laboratory in Algorithmic and Heuristic Programming, University Campus Farhat Hached, Tunis, Tunisia

    Amal Mbarki & Mohamed Naouai

Authors
  1. Amal Mbarki
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  2. Mohamed Naouai
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Corresponding author

Correspondence to Amal Mbarki .

Editor information

Editors and Affiliations

  1. Faculty of Informatics, Reutlingen University, Reutlingen, Baden-Württemberg, Germany

    Alfred Zimmermann

  2. KES International and Bournemouth University, Shoreham-by-sea, UK

    Robert J. Howlett

  3. University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Mbarki, A., Naouai, M. (2021). A Survey of Visual Perception Approaches. In: Zimmermann, A., Howlett, R., Jain, L. (eds) Human Centred Intelligent Systems. Smart Innovation, Systems and Technologies, vol 189. Springer, Singapore. https://doi.org/10.1007/978-981-15-5784-2_6

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