Yuan Gao, M. Ziegler, Frederik Zilly, Sandro Esquivel, R. Koch
{"title":"A linear method for recovering the depth of Ultra HD cameras using a kinect V2 sensor","authors":"Yuan Gao, M. Ziegler, Frederik Zilly, Sandro Esquivel, R. Koch","doi":"10.23919/MVA.2017.7986908","DOIUrl":null,"url":null,"abstract":"Depth-Image-Based Rendering (DIBR) is a mature and important method for making free-viewpoint videos. As for the study of the DIBR approach, on the one hand, most of current research focuses on how to use it in systems with low resolution cameras, while a lot of Ultra HD rendering devices have been launched into markets. On the other hand, the quality and accuracy of the depth image directly affects the final rendering result. Therefore, in this paper we try to make some improvements on solving the problem of recovering the depth information for Ultra HD cameras with the help of a Kinect V2 sensor. To this end, a linear least squares method is proposed, which recovers the rigid transformation between a Kinect V2 and an Ultra HD camera, using the depth information from the Kinect V2 sensor. In addition, a non-linear coarse-to-fine method, which is based on Sparse Bundle Adjustment (SBA), is compared with this linear method. Experiments show that our proposed method performs better than the non-linear method for the Ultra HD depth image recovery both in computing time and precision.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"934 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MVA.2017.7986908","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Depth-Image-Based Rendering (DIBR) is a mature and important method for making free-viewpoint videos. As for the study of the DIBR approach, on the one hand, most of current research focuses on how to use it in systems with low resolution cameras, while a lot of Ultra HD rendering devices have been launched into markets. On the other hand, the quality and accuracy of the depth image directly affects the final rendering result. Therefore, in this paper we try to make some improvements on solving the problem of recovering the depth information for Ultra HD cameras with the help of a Kinect V2 sensor. To this end, a linear least squares method is proposed, which recovers the rigid transformation between a Kinect V2 and an Ultra HD camera, using the depth information from the Kinect V2 sensor. In addition, a non-linear coarse-to-fine method, which is based on Sparse Bundle Adjustment (SBA), is compared with this linear method. Experiments show that our proposed method performs better than the non-linear method for the Ultra HD depth image recovery both in computing time and precision.