{"title":"基于中级轮廓特征的免费视点视频图像质量评估","authors":"Suiyi Ling, P. Callet","doi":"10.1109/ICME.2017.8019431","DOIUrl":null,"url":null,"abstract":"Free view point video (FVV), which offers immersive experience to users with multiple views, is one of the new trends in advanced visual media. These new viewpoints are traditionally synthesized via depth image-based rendering(DIBR) and geometric distortions are therefore observed. Mid-level contours descriptors are capable of evaluating such edges incoherence among the synthesized images which common image quality metrics fail to capture. In this paper, we use the concept of ‘Sketch Token’, that is a mid-level contours descriptor, and introduce a novel metric for DIBR-synthesized image quality assessment by measuring how classes of contours change after synthesis. Experiments are conducted on the IRCCyN/IVC DIBR image database and the results show that the proposed metric achieves a correlation of 88.77% which is comparable to state-of-the-art metrics like MW-PSNR and MP-PSNR.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Image quality assessment for free viewpoint video based on mid-level contours feature\",\"authors\":\"Suiyi Ling, P. Callet\",\"doi\":\"10.1109/ICME.2017.8019431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Free view point video (FVV), which offers immersive experience to users with multiple views, is one of the new trends in advanced visual media. These new viewpoints are traditionally synthesized via depth image-based rendering(DIBR) and geometric distortions are therefore observed. Mid-level contours descriptors are capable of evaluating such edges incoherence among the synthesized images which common image quality metrics fail to capture. In this paper, we use the concept of ‘Sketch Token’, that is a mid-level contours descriptor, and introduce a novel metric for DIBR-synthesized image quality assessment by measuring how classes of contours change after synthesis. Experiments are conducted on the IRCCyN/IVC DIBR image database and the results show that the proposed metric achieves a correlation of 88.77% which is comparable to state-of-the-art metrics like MW-PSNR and MP-PSNR.\",\"PeriodicalId\":330977,\"journal\":{\"name\":\"2017 IEEE International Conference on Multimedia and Expo (ICME)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Multimedia and Expo (ICME)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICME.2017.8019431\",\"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 International Conference on Multimedia and Expo (ICME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2017.8019431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
摘要
免费视点视频(Free view point video, FVV)为用户提供沉浸式的多视点体验,是高级视觉媒体发展的新趋势之一。这些新的视点传统上是通过深度图像渲染(DIBR)合成的,因此观察到几何扭曲。中级轮廓描述符能够评估一般图像质量度量无法捕获的合成图像之间的边缘不相干性。在本文中,我们使用了“Sketch Token”的概念,这是一个中级轮廓描述符,并通过测量合成后轮廓类的变化情况,引入了一种用于dibr合成图像质量评估的新度量。在IRCCyN/IVC DIBR图像数据库上进行了实验,结果表明,所提出的度量达到了88.77%的相关性,与最先进的度量如MW-PSNR和MP-PSNR相当。
Image quality assessment for free viewpoint video based on mid-level contours feature
Free view point video (FVV), which offers immersive experience to users with multiple views, is one of the new trends in advanced visual media. These new viewpoints are traditionally synthesized via depth image-based rendering(DIBR) and geometric distortions are therefore observed. Mid-level contours descriptors are capable of evaluating such edges incoherence among the synthesized images which common image quality metrics fail to capture. In this paper, we use the concept of ‘Sketch Token’, that is a mid-level contours descriptor, and introduce a novel metric for DIBR-synthesized image quality assessment by measuring how classes of contours change after synthesis. Experiments are conducted on the IRCCyN/IVC DIBR image database and the results show that the proposed metric achieves a correlation of 88.77% which is comparable to state-of-the-art metrics like MW-PSNR and MP-PSNR.