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키넥트로부터 획득된 깊이 영상의 확장을 위한 GPU 기반 채움 기법 KCI 등재

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

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한국컴퓨터게임학회 논문지 (Journal of The Korean Society for Computer Game)
한국컴퓨터게임학회 (Korean Society for Computer Game)
초록

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
  4. 구현 및 실험 결과
  5. 결론
  참고문헌
저자
  • 송민호(Department of Digital Informatics and Convergence) | Min-Ho Song
  • 류관희(Department of Computer Science Chungbuk National University) | Kwan-Hee Yoo Correspondence to