• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/
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Development of Real-Time Objects Segmentation for Dual-Camera Synthesis in iOS


Yoo-jin Jang, Ji-yeong Kim, Ju-hyun Lee, Jun Hwang, Journal of Internet Computing and Services, Vol. 22, No. 3, pp. 37-43, Jun. 2021
10.7472/jksii.2021.22.3.37, Full Text:  HTML
Keywords: OS, Semantic segmentation, depth, computer vision, Dual Camera, Mobile Application

Abstract

In this paper, we study how objects from front and back cameras can be recognized in real time in a mobile environment to segment regions of object pixels and synthesize them through image processing. To this work, we applied DeepLabV3 machine learning model to dual cameras provided by Apple's iOS. We also propose methods using Core Image and Core Graphics libraries from Apple for image synthesis and postprocessing. Furthermore, we improved CPU usage than previous works and compared the throughput rates and results of Depth and DeepLabV3. Finally, We also developed a camera application using these two methods.


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Cite this article
[APA Style]
Jang, Y., Kim, J., Lee, J., & Hwang, J. (2021). Development of Real-Time Objects Segmentation for Dual-Camera Synthesis in iOS. Journal of Internet Computing and Services, 22(3), 37-43. DOI: 10.7472/jksii.2021.22.3.37.

[IEEE Style]
Y. Jang, J. Kim, J. Lee, J. Hwang, "Development of Real-Time Objects Segmentation for Dual-Camera Synthesis in iOS," Journal of Internet Computing and Services, vol. 22, no. 3, pp. 37-43, 2021. DOI: 10.7472/jksii.2021.22.3.37.

[ACM Style]
Yoo-jin Jang, Ji-yeong Kim, Ju-hyun Lee, and Jun Hwang. 2021. Development of Real-Time Objects Segmentation for Dual-Camera Synthesis in iOS. Journal of Internet Computing and Services, 22, 3, (2021), 37-43. DOI: 10.7472/jksii.2021.22.3.37.