{"title":"多焦全光相机镜头选择过程优化及数值评价","authors":"L. Palmieri, R. Koch","doi":"10.1109/CVPRW.2017.223","DOIUrl":null,"url":null,"abstract":"The last years have seen a quick rise of digital photography. Plenoptic cameras provide extended capabilities with respect to previous models. Multi-focus cameras enlarge the depth-of-field of the pictures using different focal lengths in the lens composing the array, but questions still arise on how to select and use these lenses. In this work a further insight on the lens selection was made, and a novel method was developed in order to choose the best available lens combination for the disparity estimation. We test different lens combinations, ranking them based on the error and the number of different lenses used, creating a mapping function that relates the virtual depth with the combination that achieves the best result. The results are then organized in a look up table that can be tuned to trade off between performances and accuracy. This allows for fast and accurate lens selection. Moreover, new synthetic images with respective ground truth are provided, in order to confirm that this work performs better than the current state of the art in efficiency and accuracy of the results.","PeriodicalId":6668,"journal":{"name":"2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","volume":"33 1","pages":"1763-1774"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Optimizing the Lens Selection Process for Multi-focus Plenoptic Cameras and Numerical Evaluation\",\"authors\":\"L. Palmieri, R. Koch\",\"doi\":\"10.1109/CVPRW.2017.223\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The last years have seen a quick rise of digital photography. Plenoptic cameras provide extended capabilities with respect to previous models. Multi-focus cameras enlarge the depth-of-field of the pictures using different focal lengths in the lens composing the array, but questions still arise on how to select and use these lenses. In this work a further insight on the lens selection was made, and a novel method was developed in order to choose the best available lens combination for the disparity estimation. We test different lens combinations, ranking them based on the error and the number of different lenses used, creating a mapping function that relates the virtual depth with the combination that achieves the best result. The results are then organized in a look up table that can be tuned to trade off between performances and accuracy. This allows for fast and accurate lens selection. Moreover, new synthetic images with respective ground truth are provided, in order to confirm that this work performs better than the current state of the art in efficiency and accuracy of the results.\",\"PeriodicalId\":6668,\"journal\":{\"name\":\"2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)\",\"volume\":\"33 1\",\"pages\":\"1763-1774\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPRW.2017.223\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2017.223","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing the Lens Selection Process for Multi-focus Plenoptic Cameras and Numerical Evaluation
The last years have seen a quick rise of digital photography. Plenoptic cameras provide extended capabilities with respect to previous models. Multi-focus cameras enlarge the depth-of-field of the pictures using different focal lengths in the lens composing the array, but questions still arise on how to select and use these lenses. In this work a further insight on the lens selection was made, and a novel method was developed in order to choose the best available lens combination for the disparity estimation. We test different lens combinations, ranking them based on the error and the number of different lenses used, creating a mapping function that relates the virtual depth with the combination that achieves the best result. The results are then organized in a look up table that can be tuned to trade off between performances and accuracy. This allows for fast and accurate lens selection. Moreover, new synthetic images with respective ground truth are provided, in order to confirm that this work performs better than the current state of the art in efficiency and accuracy of the results.