방송공학회논문지 (Journal of Broadcast Engineering)

  • 제26권5호
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  • Pages.553-565
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  • 2021
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  • 1226-7953(pISSN)
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  • 2287-9137(eISSN)
한국방송∙미디어공학회 (The Korean Institute of Broadcast and Media Engineers)
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2D 및 3D DCT를 활용한 포인트 클라우드 압축 비교 실험

Comparative Experiment of 2D and 3D DCT Point Cloud Compression

  • Nam, Kwijung (Department of Electronics and Information Convergence Engineering, Kyung Hee University) ;
  • Kim, Junsik (Department of Electronics and Information Convergence Engineering, Kyung Hee University) ;
  • Han, Muhyen (YOJIN Construction&Engineering) ;
  • Kim, Kyuheon (Department of Electronics and Information Convergence Engineering, Kyung Hee University) ;
  • Hwang, Minkyu (LXsemicon)
  • 투고 : 2021.03.05
  • 심사 : 2021.08.27
  • 발행 : 2021.09.30
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초록

포인트 클라우드는 3D 오브젝트를 표현하기 위한 점들의 집합으로 3D 좌표 정보인 기하 정보와 색상, 반사율 등을 나타내는 속성 정보로 이루어져 있으며, 이러한 표현 방식으로 인해 2D 영상에 비해 방대한 양의 데이터를 가진다. 따라서, 포인트 클라우드 데이터를 전송하거나 다양한 분야에서 활용하기 위해서 포인트 클라우드 데이터를 압축하는 과정이 필수적으로 요구된다. 포인트 클라우드는 2D 영상과 같이 해당 영상을 구성하는 2D 기하 정보에 대응하는 색상 정보가 모두 존재하는 것과 달리, 3D 공간 중 일부만이 색상과 같은 속성 정보를 포함하여 포인트 클라우드를 표현하고 있기에, 기하 정보에 대한 별도의 처리도 요구된다. 이와 같은 포인트 클라우드의 특징을 기반으로 고밀도 포인트 클라우드 데이터의 압축 방안으로 국제 표준화 기구 ISO/IEC 산하 MPEG에서는 포인트 클라우드 영상을 사영한 뒤 2D DCT 기반의 2D 영상 압축 코덱으로 압축하는 V-PCC 를 표준화 중에 있다. 해당 표준은 3D 포인트 클라우드를 2D로 변환하여 압축을 진행하기에 3D 공간 정보를 정확하게 표현하기에는 한계가 존재한다. 이에, 본 논문에서는 포인트 클라우드 정지영상을 3D 상에서 3D DCT로 변환하여 포인트 클라우드 데이터를 압축하는 방안인 3D Discrete Cosine Transform based Point Cloud Compression을 제시하고, 2D DCT 기반의 V-PCC와 비교하여 3D DCT의 효율성을 확인하고자 한다.

Point cloud is a set of points for representing a 3D object, and consists of geometric information, which is 3D coordinate information, and attribute information, which is information representing color, reflectance, and the like. In this way of expressing, it has a vast amount of data compared to 2D images. Therefore, a process of compressing the point cloud data in order to transmit the point cloud data or use it in various fields is required. Unlike color information corresponding to all 2D geometric information constituting a 2D image, a point cloud represents a point cloud including attribute information such as color in only a part of the 3D space. Therefore, separate processing of geometric information is also required. Based on these characteristics of point clouds, MPEG under ISO/IEC standardizes V-PCC, which imitates point cloud images and compresses them into 2D DCT-based 2D image compression codecs, as a compression method for high-density point cloud data. This has limitations in accurately representing 3D spatial information to proceed with compression by converting 3D point clouds to 2D, and difficulty in processing non-existent points when utilizing 3D DCT. Therefore, in this paper, we present 3D Discrete Cosine Transform-based Point Cloud Compression (3DCT PCC), a method to compress point cloud data, which is a 3D image by utilizing 3D DCT, and confirm the efficiency of 3D DCT compared to V-PCC based on 2D DCT.

키워드

과제정보

This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2021-0-02046) supervised by the IITP and the Institute of Information & communications Technology Planning & evaluation (IITP) (Grant number: 2020-0-00452).

참고문헌

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