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Automatic Estimation of Illumination Features for Indoor Photorealistic Rendering in Augmented Reality

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Intelligent Software Methodologies, Tools and Techniques (SoMeT 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 532))

Abstract

In this paper, a fast and practical algorithm is presented to estimate the multiple number of lights from every single indoor scene image in Augmented Reality environmet. This algorithm provides a way to accurately estimate the position, directions, and intensities properties of the light sources in a scene. Unlike other state-of-the-art algorithms, it is able to give accurate results without any essential analysis on the objects in the scene. It uses the analysis of the saturation channel HSV data. The evaluation is done by testing a ground truth dataset of synthetic and real images with known properties of lights and then comparing the results with other studies in the field.

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Acknowledgments

This research was undertaken as part of the Research Management Center (RMC) of Universiti Teknologi Malaysia (UTM) via Science Fund grant Vot. R.J13000.7282.4S078.

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Authors and Affiliations

  1. Media and Game Innovation Centre of Excellence (MaGIC-X) UTM-IRDA, Universiti Teknologi Malaysia, 81310, Johor Bahru, Malaysia

    Hasan Alhajhamad, Mohd Shahrizal Sunar & Hoshang Kolivand

Authors
  1. Hasan Alhajhamad
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  2. Mohd Shahrizal Sunar
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  3. Hoshang Kolivand
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Corresponding author

Correspondence to Hasan Alhajhamad .

Editor information

Editors and Affiliations

  1. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  2. University of Naples "Federico II", Napoli, Italy

    Guido Guizzi

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Alhajhamad, H., Sunar, M.S., Kolivand, H. (2015). Automatic Estimation of Illumination Features for Indoor Photorealistic Rendering in Augmented Reality. In: Fujita, H., Guizzi, G. (eds) Intelligent Software Methodologies, Tools and Techniques. SoMeT 2015. Communications in Computer and Information Science, vol 532. Springer, Cham. https://doi.org/10.1007/978-3-319-22689-7_42

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  • DOI: https://doi.org/10.1007/978-3-319-22689-7_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22688-0

  • Online ISBN: 978-3-319-22689-7

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