Skip to main content

Multi-viewpoint Rendering Optimization of Indoor Scene Based on Binocular Vision

  • Conference paper
  • First Online:
Multimedia Technology and Enhanced Learning (ICMTEL 2021)

Abstract

The traditional multi-viewpoint rendering method for indoor scenes has poor lighting and shadow effects, resulting in too dark or bright indoor scene multi-viewpoint rendering. Therefore, an optimization method for indoor scene multi-viewpoint rendering based on binocular vision is proposed. This research plans light and shadow effects based on the visual relationship between point light sources and indoor scenes; sets rendering points based on binocular vision; and renders indoor scenes with multiple viewpoint angles. The simulation experiment results show that compared with the traditional rendering method, the light and shadow effect of the studied method is excellent, and the rendered indoor scene is suitable for light and dark.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Mengyu, J., Ligang, L.: Multi view rendering optimization of indoor scene based on perception. J Univ. Sci. Technol. China 48(2), 140–147 (2018)

    Google Scholar 

  2. Ziyu, W., Yingmin, Z., Yongbin, C., et al.: Optimization of indoor scene semantic segmentation network based on rgb-d image. Automation Information Eng 2, 27–32 (2020)

    Google Scholar 

  3. An, Z., Li, F., Wan, G., et al.: Construction method of indoor and outdoor scene based on BIM and GIS. Digital design 1, 2020, 009 (001):151–153.

    Google Scholar 

  4. Chen, X., Li, P.: Analysis of the light and shadow in the modern architecture’s expression. China Illuminating Eng. J 29(01), 82–86 (2018)

    Google Scholar 

  5. Fu, P., Chen, X., Wu, L.: Research on absolute positioning of binocular vision based on corner. J. Electr. Measur. Instrument 32(03), 1–8 (2018)

    Google Scholar 

  6. Liu, Y., Wang, Z., Liu, Y., et al.: Reversing obstacle detection based on binocular vision image. J. Chongqing Jiaotong Univ. 37(3), 92–98 (2018)

    Google Scholar 

  7. Sun, S., Sun, S.: Precision matching simulation of binocular stereo vision target. Comput. Simul. 35(11), 413–416 (2018)

    Google Scholar 

  8. Liu, S., Liu, D., Srivastava, G., Połap, D., Woźniak, M.: Overview and methods of correlation filter algorithms in object tracking. Complex Intelligent Syst (2020). https://doi.org/10.1007/s40747-020-00161-4

    Article  Google Scholar 

  9. Fu, W., Liu, S., Srivastava, G.: Optimization of big data scheduling in social networks[J]. Entropy 21(9), 902 (2019)

    Article  MathSciNet  Google Scholar 

  10. Liu, S., Bai, W., Zeng, N., et al.: A fast fractal based compression for MRI images[J]. IEEE Access 7, 62412–62420 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Jing, H. (2021). Multi-viewpoint Rendering Optimization of Indoor Scene Based on Binocular Vision. In: Fu, W., Xu, Y., Wang, SH., Zhang, Y. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 388. Springer, Cham. https://doi.org/10.1007/978-3-030-82565-2_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-82565-2_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-82564-5

  • Online ISBN: 978-3-030-82565-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics