{"title":"Guest Editors' Introduction to the Special Section on Computational Photography","authors":"Ayan Chakrabarti, Kalyan Sunkavalli, D. Forsyth","doi":"10.1109/tpami.2020.2993888","DOIUrl":null,"url":null,"abstract":"The nine papers in this special section focus on computational photography. The development of increasingly successful visual inference algorithms has driven progress in a number of different application domains—ranging from photography to autonomous vehicles to graphics and virtual reality systems. As we continue to extend the capabilities of these computational algorithms, a complementary research direction lies in asking what the right visual measurements are for these algorithms to operate on. In computational photography, we seek to investigate both components—computational and sensory—of intelligent visual systems in synergy, to build measurement schemes and inference algorithms that are jointly optimal for a desired task, and thus create functionalities that go beyond what is possible with traditional cameras and computational tools. The call for papers for this section was co-ordinated with the 2020 IEEE International Conference on Computational Photography (ICCP) that was held from April 24-26, 2020.","PeriodicalId":13207,"journal":{"name":"IEEE Trans. Pattern Anal. Mach. Intell.","volume":"112 1","pages":"1545-1546"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Trans. Pattern Anal. Mach. Intell.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/tpami.2020.2993888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The nine papers in this special section focus on computational photography. The development of increasingly successful visual inference algorithms has driven progress in a number of different application domains—ranging from photography to autonomous vehicles to graphics and virtual reality systems. As we continue to extend the capabilities of these computational algorithms, a complementary research direction lies in asking what the right visual measurements are for these algorithms to operate on. In computational photography, we seek to investigate both components—computational and sensory—of intelligent visual systems in synergy, to build measurement schemes and inference algorithms that are jointly optimal for a desired task, and thus create functionalities that go beyond what is possible with traditional cameras and computational tools. The call for papers for this section was co-ordinated with the 2020 IEEE International Conference on Computational Photography (ICCP) that was held from April 24-26, 2020.