Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, G. Lafruit
{"title":"非lambertian对象的多项式图像渲染","authors":"Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, G. Lafruit","doi":"10.1109/VCIP53242.2021.9675371","DOIUrl":null,"url":null,"abstract":"Non-Lambertian objects present an aspect which depends on the viewer's position towards the surrounding scene. Contrary to diffuse objects, their features move non-linearly with the camera, preventing rendering them with existing Depth Image-Based Rendering (DIBR) approaches, or to triangulate their surface with Structure-from-Motion (SfM). In this paper, we propose an extension of the DIBR paradigm to describe these non-linearities, by replacing the depth maps by more complete multi-channel “non-Lambertian maps”, without attempting a 3D reconstruction of the scene. We provide a study of the importance of each coefficient of the proposed map, measuring the trade-off between visual quality and data volume to optimally render non-Lambertian objects. We compare our method to other state-of-the-art image-based rendering methods and outperform them with promising subjective and objective results on a challenging dataset.","PeriodicalId":114062,"journal":{"name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Polynomial Image-Based Rendering for non-Lambertian Objects\",\"authors\":\"Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, G. Lafruit\",\"doi\":\"10.1109/VCIP53242.2021.9675371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Non-Lambertian objects present an aspect which depends on the viewer's position towards the surrounding scene. Contrary to diffuse objects, their features move non-linearly with the camera, preventing rendering them with existing Depth Image-Based Rendering (DIBR) approaches, or to triangulate their surface with Structure-from-Motion (SfM). In this paper, we propose an extension of the DIBR paradigm to describe these non-linearities, by replacing the depth maps by more complete multi-channel “non-Lambertian maps”, without attempting a 3D reconstruction of the scene. We provide a study of the importance of each coefficient of the proposed map, measuring the trade-off between visual quality and data volume to optimally render non-Lambertian objects. We compare our method to other state-of-the-art image-based rendering methods and outperform them with promising subjective and objective results on a challenging dataset.\",\"PeriodicalId\":114062,\"journal\":{\"name\":\"2021 International Conference on Visual Communications and Image Processing (VCIP)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Visual Communications and Image Processing (VCIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VCIP53242.2021.9675371\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Visual Communications and Image Processing (VCIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP53242.2021.9675371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Polynomial Image-Based Rendering for non-Lambertian Objects
Non-Lambertian objects present an aspect which depends on the viewer's position towards the surrounding scene. Contrary to diffuse objects, their features move non-linearly with the camera, preventing rendering them with existing Depth Image-Based Rendering (DIBR) approaches, or to triangulate their surface with Structure-from-Motion (SfM). In this paper, we propose an extension of the DIBR paradigm to describe these non-linearities, by replacing the depth maps by more complete multi-channel “non-Lambertian maps”, without attempting a 3D reconstruction of the scene. We provide a study of the importance of each coefficient of the proposed map, measuring the trade-off between visual quality and data volume to optimally render non-Lambertian objects. We compare our method to other state-of-the-art image-based rendering methods and outperform them with promising subjective and objective results on a challenging dataset.