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Journal Article
딥러닝기반 입체 영상의 획득 및 처리 기술 동향
- Authors
- 윤민성
- Issue Date
- 2020-10
- Citation
- 전자통신동향분석, v.35, no.5, pp.112-122
- ISSN
- 1225-6455
- Publisher
- 한국전자통신연구원
- Language
- Korean
- Type
- Journal Article
- Abstract
- In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject’s surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.
- KSP Keywords
- 3D computer graphics, 3D data, 3D image processing, 3d modeling, Active illumination, Autonomous Vehicle Navigation, Computing power, Convolution neural network(CNN), Data analysis methods, Depth Map, Depth camera
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
