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논문검색

키넥트로부터 획득된 깊이 영상의 확장을 위한 GPU 기반 채움 기법

원문정보

GPU Based Filling Methods for Expansion of Depth Image Captured by Kinect

송민호, 류관희

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

Three-dimensional(3D) display technique is widely used in our daily life. Especially, to product augmented game contents which can interact with users, it is necessary to get high quality resolution image data to reconstruct 3D model more exquisitely. In this paper, we tried to expand depth image captured by Kinect using various interpolation methods(nearest neighbor, bilinear, bicubic) to adapt it to the size of original Kinect color image. To measure the quality of expanded depth image compared to original depth image, we used PSNR(Peak Signal-to-noise ratio) index. Besides, we implemented GPU parallel processing algorithm with OpenCL to interpolate a large amount of image data rapidly. As a result of the experiment, a bicubic interpolation method made an accurate depth image although it had a long time.

목차

ABSTRACT
 1. 서론
 2. 관련연구 및 문제점
 3. GPU 기반 확장된 깊이영상의 채움기법
  3.1 최근방 이웃 보간법
  3.2 양선형 보간법
  3.3 양3차 회선 보간법
  3.4 GPU 기반의 깊이영상 보간 기법 처리
 4. 구현 및 실험 결과
 5. 결론
 참고문헌

저자정보

  • 송민호 Min-Ho Song. Department of Digital Informatics and Convergence
  • 류관희 Kwan-Hee Yoo. Department of Computer Science Chungbuk National University

참고문헌

자료제공 : 네이버학술정보

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