2016 IEEE International Conference on Computational Photography (ICCP)最新文献_第2页

3D reconstruction of mirror-type objects using efficient ray coding 使用高效光线编码的镜面型物体的三维重建

2016 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2016-05-13 DOI: 10.1109/ICCPHOT.2016.7492867

S. Tin, Jinwei Ye, M. Nezamabadi, Can Chen

引用次数: 14

Shape and reflectance from two-bounce light transients 双反射光瞬态的形状和反射率

2016 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2016-05-13 DOI: 10.1109/ICCPHOT.2016.7492882

Chia-Yin Tsai, A. Veeraraghavan, Aswin C. Sankaranarayanan

引用次数: 6

Learning joint demosaicing and denoising based on sequential energy minimization 学习基于顺序能量最小化的联合去马赛克和去噪

2016 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2016-05-13 DOI: 10.1109/ICCPHOT.2016.7492871

Teresa Klatzer, K. Hammernik, Patrick Knöbelreiter, T. Pock

{"title":"Learning joint demosaicing and denoising based on sequential energy minimization","authors":"Teresa Klatzer, K. Hammernik, Patrick Knöbelreiter, T. Pock","doi":"10.1109/ICCPHOT.2016.7492871","DOIUrl":"https://doi.org/10.1109/ICCPHOT.2016.7492871","url":null,"abstract":"Demosaicing is an important first step for color image acquisition. For practical reasons, demosaicing algorithms have to be both efficient and yield high quality results in the presence of noise. The demosaicing problem poses several challenges, e.g. zippering and false color artifacts as well as edge blur. In this work, we introduce a novel learning based method that can overcome these challenges. We formulate demosaicing as an image restoration problem and propose to learn efficient regularization inspired by a variational energy minimization framework that can be trained for different sensor layouts. Our algorithm performs joint demosaicing and denoising in close relation to the real physical mosaicing process on a camera sensor. This is achieved by learning a sequence of energy minimization problems composed of a set of RGB filters and corresponding activation functions. We evaluate our algorithm on the Microsoft Demosaicing data set in terms of peak signal to noise ratio (PSNR) and structured similarity index (SSIM). Our algorithm is highly efficient both in image quality and run time. We achieve an improvement of up to 2.6 dB over recent state-of-the-art algorithms.","PeriodicalId":156635,"journal":{"name":"2016 IEEE International Conference on Computational Photography (ICCP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130692591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 74

4D light field segmentation with spatial and angular consistencies 具有空间和角度一致性的四维光场分割

2016 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2016-05-13 DOI: 10.1109/ICCPHOT.2016.7492872

H. Mihara, Takuya Funatomi, Kenichiro Tanaka, Hiroyuki Kubo, Y. Mukaigawa, H. Nagahara

引用次数: 29

Towards flexible sheet cameras: Deformable lens arrays with intrinsic optical adaptation 面向柔性薄片相机:具有内在光学适应性的可变形透镜阵列

2016 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2016-05-13 DOI: 10.1109/ICCPHOT.2016.7492876

Daniel C. Sims, Yonghao Yue, S. Nayar

{"title":"Towards flexible sheet cameras: Deformable lens arrays with intrinsic optical adaptation","authors":"Daniel C. Sims, Yonghao Yue, S. Nayar","doi":"10.1109/ICCPHOT.2016.7492876","DOIUrl":"https://doi.org/10.1109/ICCPHOT.2016.7492876","url":null,"abstract":"We propose a framework for developing a new class of imaging systems that are thin and flexible. Such an imaging sheet can be flexed at will and wrapped around everyday objects to capture unconventional fields of view. Our approach is to use a lens array attached to a sheet with a 2D grid of pixels. A major challenge with this type of a system is that its sampling of the scene varies with the curvature of the sheet. To avoid undesirable aliasing effects due to under-sampling in high curvature regions of the sheet, we design a deformable lens array with adaptive optical properties. We show that the material and geometric properties of the lens array can be optimized so that the object-side point spread function corresponding to each pixel widens with the curvature of the sheet at that pixel. This intrinsic adaptation of focal length is passive (without the use of actuators or other control mechanisms), and enables a sheet camera to capture images without aliasing, irrespective of its shape. We have designed a 33×33 lens array, fabricated it using silicone rubber, and conducted several experiments to verify its optical adaptation characteristics. We conclude with a discussion on the advantages of our proposed approach as well as future work.","PeriodicalId":156635,"journal":{"name":"2016 IEEE International Conference on Computational Photography (ICCP)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132879782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Do-it-yourself lighting design for product videography 为产品摄像做自己的灯光设计

2016 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2016-05-13 DOI: 10.1109/ICCPHOT.2016.7492878

Ivaylo Boyadzhiev, Jiawen Chen, Sylvain Paris, K. Bala

{"title":"Do-it-yourself lighting design for product videography","authors":"Ivaylo Boyadzhiev, Jiawen Chen, Sylvain Paris, K. Bala","doi":"10.1109/ICCPHOT.2016.7492878","DOIUrl":"https://doi.org/10.1109/ICCPHOT.2016.7492878","url":null,"abstract":"The growth of online marketplaces for selling goods has increased the need for product photography by novice users and consumers. Additionally, the increased use of online media and large-screen billboards promotes the adoption of videos for advertising, going beyond just using still imagery. Lighting is a key distinction between professional and casual product videography. Professionals use specialized hardware setups, and bring expert skills to create good lighting that shows off the product's shape and material, while also producing aesthetically pleasing results. In this paper, we introduce a new do-it-yourself (DIY) approach to lighting design that lets novice users create studio quality product videography. We identify design principles to light products through emphasizing highlights, rim lighting, and contours. We devise a set of computational metrics to achieve these design goals. Our workflow is: the user acquires a video of the product by mounting a video camera on a tripod and using a tablet to light objects by waving the tablet around the object. We automatically analyze and split this acquired video into snippets that match our design principles. Finally, we present an interface that lets users easily select snippets with specific characteristics and then assembles them to produce a final pleasing video of the product. Alternatively, they can rely on our template mechanism to automatically assemble a video.","PeriodicalId":156635,"journal":{"name":"2016 IEEE International Conference on Computational Photography (ICCP)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123833758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

In-situ multi-view multi-scattering stochastic tomography 原位多视点多散射随机层析成像

2016 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2016-05-13 DOI: 10.1109/ICCPHOT.2016.7492869

Vadim Holodovsky, Y. Schechner, Anat Levin, Aviad Levis, Amit Aides

引用次数: 29