Light field imaging is an emerging technology in computational photography areas. Based on innovative designs of the imaging model and the optical path, light field cameras not only record the spatial intensity of thr...Light field imaging is an emerging technology in computational photography areas. Based on innovative designs of the imaging model and the optical path, light field cameras not only record the spatial intensity of three- dimensional （3D） objects, but also capture the angular information of the physical world, which provides new ways to address various problems in computer vision, such as 3D reconstruction, saliency detection, and object recognition. In this paper, three key aspects of light field cameras, i.e., model, calibration, and reconstruction, are reviewed extensively. Furthermore, light field based applications on informatics, physics, medicine, and biology are exhibited. Finally, open issues in light field imaging and long-term application prospects in other natural sciences are discussed.展开更多
Light field rendering is an image-based rendering method that does not use 3 D models but only images of the scene as input to render new views.Light field approximation,represented as a set of images,suffers from so-...Light field rendering is an image-based rendering method that does not use 3 D models but only images of the scene as input to render new views.Light field approximation,represented as a set of images,suffers from so-called refocusing artifacts due to different depth values of the pixels in the scene.Without information about depths in the scene,proper focusing of the light field scene is limited to a single focusing distance.The correct focusing method is addressed in this work and a real-time solution is proposed for focusing of light field scenes,based on statistical analysis of the pixel values contributing to the final image.Unlike existing techniques,this method does not need precomputed or acquired depth information.Memory requirements and streaming bandwidth are reduced and real-time rendering is possible even for high resolution light field data,yielding visually satisfactory results.Experimental evaluation of the proposed method,implemented on a GPU,is presented in this paper.展开更多
基金Project supported by the National Natural Science Foundation of China （Nos. 61531014 and 61272287）
文摘Light field imaging is an emerging technology in computational photography areas. Based on innovative designs of the imaging model and the optical path, light field cameras not only record the spatial intensity of three- dimensional （3D） objects, but also capture the angular information of the physical world, which provides new ways to address various problems in computer vision, such as 3D reconstruction, saliency detection, and object recognition. In this paper, three key aspects of light field cameras, i.e., model, calibration, and reconstruction, are reviewed extensively. Furthermore, light field based applications on informatics, physics, medicine, and biology are exhibited. Finally, open issues in light field imaging and long-term application prospects in other natural sciences are discussed.
基金supported by The Ministry of Education,Youth and Sports from the National Programme of Sustainability(NPU II)project IT4Innovations excellence in science,LQ1602。
文摘Light field rendering is an image-based rendering method that does not use 3 D models but only images of the scene as input to render new views.Light field approximation,represented as a set of images,suffers from so-called refocusing artifacts due to different depth values of the pixels in the scene.Without information about depths in the scene,proper focusing of the light field scene is limited to a single focusing distance.The correct focusing method is addressed in this work and a real-time solution is proposed for focusing of light field scenes,based on statistical analysis of the pixel values contributing to the final image.Unlike existing techniques,this method does not need precomputed or acquired depth information.Memory requirements and streaming bandwidth are reduced and real-time rendering is possible even for high resolution light field data,yielding visually satisfactory results.Experimental evaluation of the proposed method,implemented on a GPU,is presented in this paper.
