Real-Time Shading Image Implementation Technology for Physical Viod Display

  • Authors

    • Eun Seo Song
    • Gi Tae Kim
    • Sung Dae Hong
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.18779
  • Flip Display, Shading image, physical display, RGB-D sensor, Real-Time Interaction Image Control

  • Abstract

    Background/Objectives: The purpose of this study is control technology to reflect user's appearance and movement in the void display in real time.

    Methods/Statistical analysis: In this paper, we have developed real-time shading image data acquisition based on RGB-D sensor and real-time interaction image control structure for realizing 0-255 Depth image of physical void display. We also study integrated interlocking control solution for integrated interlocking of hardware and software.

    Findings: Conventional flip displays show data in 0,1 image representation. On the other hand, the void display we are studying acquires real-time data based on RGB-D and shows the data in depth 0-255 image representation.

    Improvements/Applications: In the void display, the image representation of 0.1 was extended to the depth 0-255 representation.

  • References

    1. [1] Luigi Pagliarini., Henrik Hautop Lind. (2009). The development of robot art. Artif Life Robotics, 13(2), 401-405.

      [2] Troila. (2008). Retrieved fromhttps://troika.uk.com/project/cloud/.

      [3] Thresholding (image processing). (2018). Retrieved fromhttps://en.wikipedia.org/wiki/Thresholding_(image_processing).

      [4] Kevin LaiEmail author., Liefeng Bo., Xiaofeng Ren., Dieter Fox. (2013). RGB-D Object Recognition: Features, Algorithms, and a Large Scale Benchmark.Consumer Depth Cameras for Computer Vision, 167-192.

      [5] Andreas Eitel., Jost Tobias Springenberg., Luciano Spinello., Martin Riedmiller., Wolfram Burgard. (2015). Multimodal Deep Learning for Robust RGB-D Object Recognition. Retrieved fromhttp://ais.informatik.uni-freiburg.de/publications/papers/eitel15iros.pdf.

      [6] Kinect. (2018). Retrieved fromhttps://en.wikipedia.org/wiki/Kinect.

      [7] Tarun Kumar., Karun Verma. (2010). A theory based on conversion of RGB image to Gray image. International Journal of Computer Applications. Retrieved fromhttps://www.researchgate.net/profile/Karun_Verma/publication/46286639_A_Theory_Based_on_Conversion_of_RGB_image_to_Gray_image/links/5704a3b008ae44d70ee0662c.pdf.

      [8] Grayscale. (2018). https://en.wikipedia.org/wiki/Grayscale.

      [9] Rest API tutorial. (2017). Retrieved fromhttps://restfulapi.net/.

      [10] Marc Pollefeys. (2003). Projective 2D geometry(coure3) lecture PPT for Multiple view geometry. Retrieved fromhttps://www.cs.unc.edu/~marc/mvg/slides.html.

  • Downloads

  • How to Cite

    Seo Song, E., Tae Kim, G., & Dae Hong, S. (2018). Real-Time Shading Image Implementation Technology for Physical Viod Display. International Journal of Engineering & Technology, 7(3.34), 86-90. https://doi.org/10.14419/ijet.v7i3.34.18779

    Received date: 2018-09-02

    Accepted date: 2018-09-02

    Published date: 2018-09-01