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Augmented Reality Service Based on Object Pose Prediction Using PnP Algorithm

  • Kim, In-Seon (Department of Smart System, Kwangwoon University) ;
  • Jung, Tae-Won (Department of Immersive Content Convergence, Kwangwoon University) ;
  • Jung, Kye-Dong (Ingenium College of Liberal Arts, Kwangwoon University)
  • Received : 2021.10.26
  • Accepted : 2021.12.07
  • Published : 2021.12.31

Abstract

Digital media technology is gradually developing with the development of convergence quaternary industrial technology and mobile devices. The combination of deep learning and augmented reality can provide more convenient and lively services through the interaction of 3D virtual images with the real world. We combine deep learning-based pose prediction with augmented reality technology. We predict the eight vertices of the bounding box of the object in the image. Using the predicted eight vertices(x,y), eight vertices(x,y,z) of 3D mesh, and the intrinsic parameter of the smartphone camera, we compute the external parameters of the camera through the PnP algorithm. We calculate the distance to the object and the degree of rotation of the object using the external parameter and apply to AR content. Our method provides services in a web environment, making it highly accessible to users and easy to maintain the system. As we provide augmented reality services using consumers' smartphone cameras, we can apply them to various business fields.

Keywords

Acknowledgement

This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2020-0-00192, Development of Open Anchor-based AR Cloud for Universal Mixed Reality Service)

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