Image-Based Rendering （IBR） is one powerful approach for generating virtual views. It can provide convincing animations without an explicit geometric representation. In this paper, several implementations of light f...Image-Based Rendering （IBR） is one powerful approach for generating virtual views. It can provide convincing animations without an explicit geometric representation. In this paper, several implementations of light field rendering are summa- rized from prior arts. Several characteristics, such as the regu- lar pattern in Epipolar Plane Images （EPIs）, of light field are explored with detail under 1D parallel camera arrangement. It is proved that it is quite efficient to synthesize virtual views for Super Multi-View （SMV） application, which is in the third phase of Free- Viewpoint Television （FTV）. In comparison with convolutional stereo matching method, in which the inter- mediate view is synthesized by the two adjacent views, light field rendering makes use of more views supplied to get the high-quality views.展开更多
Light field(LF)imaging has attracted attention because of its ability to solve computer vision problems.In this paper we briefly review the research progress in computer vision in recent years.For most factors that af...Light field(LF)imaging has attracted attention because of its ability to solve computer vision problems.In this paper we briefly review the research progress in computer vision in recent years.For most factors that affect computer vision development,the richness and accuracy of visual information acquisition are decisive.LF imaging technology has made great contributions to computer vision because it uses cameras or microlens arrays to record the position and direction information of light rays,acquiring complete three-dimensional(3D)scene information.LF imaging technology improves the accuracy of depth estimation,image segmentation,blending,fusion,and 3D reconstruction.LF has also been innovatively applied to iris and face recognition,identification of materials and fake pedestrians,acquisition of epipolar plane images,shape recovery,and LF microscopy.Here,we further summarize the existing problems and the development trends of LF imaging in computer vision,including the establishment and evaluation of the LF dataset,applications under high dynamic range(HDR)conditions,LF image enhancement,virtual reality,3D display,and 3D movies,military optical camouflage technology,image recognition at micro-scale,image processing method based on HDR,and the optimal relationship between spatial resolution and four-dimensional(4D)LF information acquisition.LF imaging has achieved great success in various studies.Over the past 25 years,more than 180 publications have reported the capability of LF imaging in solving computer vision problems.We summarize these reports to make it easier for researchers to search the detailed methods for specific solutions.展开更多
文摘Image-Based Rendering （IBR） is one powerful approach for generating virtual views. It can provide convincing animations without an explicit geometric representation. In this paper, several implementations of light field rendering are summa- rized from prior arts. Several characteristics, such as the regu- lar pattern in Epipolar Plane Images （EPIs）, of light field are explored with detail under 1D parallel camera arrangement. It is proved that it is quite efficient to synthesize virtual views for Super Multi-View （SMV） application, which is in the third phase of Free- Viewpoint Television （FTV）. In comparison with convolutional stereo matching method, in which the inter- mediate view is synthesized by the two adjacent views, light field rendering makes use of more views supplied to get the high-quality views.
基金Project supported by the National Natural Science Foundation of China(Nos.61906133,62020106004,and 92048301)。
文摘Light field(LF)imaging has attracted attention because of its ability to solve computer vision problems.In this paper we briefly review the research progress in computer vision in recent years.For most factors that affect computer vision development,the richness and accuracy of visual information acquisition are decisive.LF imaging technology has made great contributions to computer vision because it uses cameras or microlens arrays to record the position and direction information of light rays,acquiring complete three-dimensional(3D)scene information.LF imaging technology improves the accuracy of depth estimation,image segmentation,blending,fusion,and 3D reconstruction.LF has also been innovatively applied to iris and face recognition,identification of materials and fake pedestrians,acquisition of epipolar plane images,shape recovery,and LF microscopy.Here,we further summarize the existing problems and the development trends of LF imaging in computer vision,including the establishment and evaluation of the LF dataset,applications under high dynamic range(HDR)conditions,LF image enhancement,virtual reality,3D display,and 3D movies,military optical camouflage technology,image recognition at micro-scale,image processing method based on HDR,and the optimal relationship between spatial resolution and four-dimensional(4D)LF information acquisition.LF imaging has achieved great success in various studies.Over the past 25 years,more than 180 publications have reported the capability of LF imaging in solving computer vision problems.We summarize these reports to make it easier for researchers to search the detailed methods for specific solutions.
