ColorCodeAR: Large identifiable ColorCode-based augmented reality system

Seungho Chae; Jonghoon Seo; Yoonsik Yang; Tack Don Han

doi:10.1109/SMC.2016.7844630

ColorCodeAR: Large identifiable ColorCode-based augmented reality system

Seungho Chae, Jonghoon Seo, Yoonsik Yang, Tack Don Han

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

Augmented reality (AR) is widely used in various applications of computer vision, such as marker-based AR and markerless-based AR. These AR techniques are used in various fields, including industry, education, and medicine. Using marker-based AR, employees can easily perform step-by-step maintenance and repairs, and they can register parts information for large plants. However, conventional marker-based AR relies on a relatively small number of recognizable IDs compared to barcode markers. In this paper, to address the insufficient identification volume in conventional AR systems, we integrate barcode-based code technology with marker-based AR technology. Based on the results of an experiment, we applied ColorCode to our marker-based AR system. Nevertheless, difficulties arise when applying ColorCode to an AR system, owing to its recognition distance and relatively small size, compared to other AR codes. In this paper, therefore, we complemented quad detection with a tracking technique for various angles and distances, facilitating reliable recognition of the color-code-based AR system, Moreover, we added a tracking module to address the system's failure to detect markers. The experimental results demonstrate that the proposed system offers stable recognition.

Original language	English
Title of host publication	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2598-2602
Number of pages	5
ISBN (Electronic)	9781509018970
DOIs	https://doi.org/10.1109/SMC.2016.7844630
Publication status	Published - 2017 Feb 6
Event	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary Duration: 2016 Oct 9 → 2016 Oct 12

Publication series

Name	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

Other

Other	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Country/Territory	Hungary
City	Budapest
Period	16/10/9 → 16/10/12

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MEST) (No. NRF-2015R1A2A1A10055673)

Publisher Copyright:
© 2016 IEEE.

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition
Artificial Intelligence
Control and Optimization
Human-Computer Interaction

Access to Document

10.1109/SMC.2016.7844630

Cite this

Chae, S., Seo, J., Yang, Y., & Han, T. D. (2017). ColorCodeAR: Large identifiable ColorCode-based augmented reality system. In 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings (pp. 2598-2602). [7844630] (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2016.7844630

Chae, Seungho ; Seo, Jonghoon ; Yang, Yoonsik et al. / ColorCodeAR : Large identifiable ColorCode-based augmented reality system. 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2598-2602 (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings).

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title = "ColorCodeAR: Large identifiable ColorCode-based augmented reality system",

abstract = "Augmented reality (AR) is widely used in various applications of computer vision, such as marker-based AR and markerless-based AR. These AR techniques are used in various fields, including industry, education, and medicine. Using marker-based AR, employees can easily perform step-by-step maintenance and repairs, and they can register parts information for large plants. However, conventional marker-based AR relies on a relatively small number of recognizable IDs compared to barcode markers. In this paper, to address the insufficient identification volume in conventional AR systems, we integrate barcode-based code technology with marker-based AR technology. Based on the results of an experiment, we applied ColorCode to our marker-based AR system. Nevertheless, difficulties arise when applying ColorCode to an AR system, owing to its recognition distance and relatively small size, compared to other AR codes. In this paper, therefore, we complemented quad detection with a tracking technique for various angles and distances, facilitating reliable recognition of the color-code-based AR system, Moreover, we added a tracking module to address the system's failure to detect markers. The experimental results demonstrate that the proposed system offers stable recognition.",

author = "Seungho Chae and Jonghoon Seo and Yoonsik Yang and Han, {Tack Don}",

note = "Funding Information: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MEST) (No. NRF-2015R1A2A1A10055673) Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 ; Conference date: 09-10-2016 Through 12-10-2016",

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Chae, S, Seo, J, Yang, Y & Han, TD 2017, ColorCodeAR: Large identifiable ColorCode-based augmented reality system. in 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings., 7844630, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 2598-2602, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, 16/10/9. https://doi.org/10.1109/SMC.2016.7844630

ColorCodeAR: Large identifiable ColorCode-based augmented reality system. / Chae, Seungho; Seo, Jonghoon; Yang, Yoonsik et al.
2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2598-2602 7844630 (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Chae, Seungho

AU - Seo, Jonghoon

AU - Yang, Yoonsik

AU - Han, Tack Don

N1 - Funding Information: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MEST) (No. NRF-2015R1A2A1A10055673) Publisher Copyright: © 2016 IEEE.

PY - 2017/2/6

Y1 - 2017/2/6

N2 - Augmented reality (AR) is widely used in various applications of computer vision, such as marker-based AR and markerless-based AR. These AR techniques are used in various fields, including industry, education, and medicine. Using marker-based AR, employees can easily perform step-by-step maintenance and repairs, and they can register parts information for large plants. However, conventional marker-based AR relies on a relatively small number of recognizable IDs compared to barcode markers. In this paper, to address the insufficient identification volume in conventional AR systems, we integrate barcode-based code technology with marker-based AR technology. Based on the results of an experiment, we applied ColorCode to our marker-based AR system. Nevertheless, difficulties arise when applying ColorCode to an AR system, owing to its recognition distance and relatively small size, compared to other AR codes. In this paper, therefore, we complemented quad detection with a tracking technique for various angles and distances, facilitating reliable recognition of the color-code-based AR system, Moreover, we added a tracking module to address the system's failure to detect markers. The experimental results demonstrate that the proposed system offers stable recognition.

AB - Augmented reality (AR) is widely used in various applications of computer vision, such as marker-based AR and markerless-based AR. These AR techniques are used in various fields, including industry, education, and medicine. Using marker-based AR, employees can easily perform step-by-step maintenance and repairs, and they can register parts information for large plants. However, conventional marker-based AR relies on a relatively small number of recognizable IDs compared to barcode markers. In this paper, to address the insufficient identification volume in conventional AR systems, we integrate barcode-based code technology with marker-based AR technology. Based on the results of an experiment, we applied ColorCode to our marker-based AR system. Nevertheless, difficulties arise when applying ColorCode to an AR system, owing to its recognition distance and relatively small size, compared to other AR codes. In this paper, therefore, we complemented quad detection with a tracking technique for various angles and distances, facilitating reliable recognition of the color-code-based AR system, Moreover, we added a tracking module to address the system's failure to detect markers. The experimental results demonstrate that the proposed system offers stable recognition.

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DO - 10.1109/SMC.2016.7844630

M3 - Conference contribution

AN - SCOPUS:85015751542

T3 - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

SP - 2598

EP - 2602

BT - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 9 October 2016 through 12 October 2016

ER -

Chae S, Seo J, Yang Y, Han TD. ColorCodeAR: Large identifiable ColorCode-based augmented reality system. In 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2598-2602. 7844630. (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings). doi: 10.1109/SMC.2016.7844630

ColorCodeAR: Large identifiable ColorCode-based augmented reality system

Abstract

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