基于视差图的三维图像重定向深度失真评分估计

M. Jagtap, R. Tripathi, Jawalkar Dinesh Kumar
{"title":"基于视差图的三维图像重定向深度失真评分估计","authors":"M. Jagtap, R. Tripathi, Jawalkar Dinesh Kumar","doi":"10.1109/SMART50582.2020.9337085","DOIUrl":null,"url":null,"abstract":"Depth distortion in an image yields some geometric errors which leads certain image quality degradation. Therefore, it is important to enhance the depth information in the left as well as right stereo images and achieve them in a substantial way. The Disparity Map Acquisition (DMA) algorithm gives rise to the depth distortion with improved disparity matrix. In this paper, we emphasis on depth score enhancement in 3D stereo images retargeting to accomplish the acceptable 3D images with improved depth distortion score. The experimental results show the stereo seam carving which deconsideres the unwanted image patches in order to generate an acceptable 3D stereo images. The obtained 3D stereo images are widely used in the applications of 3D animated movies by abolishing the blurriness in the stereo images and generate the images where the users can relish with the better visual effects. This may lead to the non-usability of 3D sterilize googles and eventually helps and reduces the burden on Indian economy.","PeriodicalId":129946,"journal":{"name":"2020 9th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Depth Distortion Score Estimation in 3-D Image Retargeting using Disparity Map\",\"authors\":\"M. Jagtap, R. Tripathi, Jawalkar Dinesh Kumar\",\"doi\":\"10.1109/SMART50582.2020.9337085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Depth distortion in an image yields some geometric errors which leads certain image quality degradation. Therefore, it is important to enhance the depth information in the left as well as right stereo images and achieve them in a substantial way. The Disparity Map Acquisition (DMA) algorithm gives rise to the depth distortion with improved disparity matrix. In this paper, we emphasis on depth score enhancement in 3D stereo images retargeting to accomplish the acceptable 3D images with improved depth distortion score. The experimental results show the stereo seam carving which deconsideres the unwanted image patches in order to generate an acceptable 3D stereo images. The obtained 3D stereo images are widely used in the applications of 3D animated movies by abolishing the blurriness in the stereo images and generate the images where the users can relish with the better visual effects. This may lead to the non-usability of 3D sterilize googles and eventually helps and reduces the burden on Indian economy.\",\"PeriodicalId\":129946,\"journal\":{\"name\":\"2020 9th International Conference System Modeling and Advancement in Research Trends (SMART)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 9th International Conference System Modeling and Advancement in Research Trends (SMART)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMART50582.2020.9337085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 9th International Conference System Modeling and Advancement in Research Trends (SMART)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMART50582.2020.9337085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

图像的深度失真会产生一些几何误差,从而导致图像质量的下降。因此,对左右立体图像的深度信息进行增强和实质性的实现是十分重要的。视差图获取(DMA)算法对视差矩阵进行了改进,导致深度失真。本文重点研究了三维立体图像重定向中的深度分数增强,以获得具有改进深度失真分数的可接受的三维图像。实验结果表明,立体缝刻方法能够去除不需要的图像斑块,从而生成可接受的三维立体图像。所获得的三维立体图像消除了立体图像的模糊性,产生的图像具有更好的视觉效果,被广泛应用于三维动画电影的应用中。这可能会导致3D消毒谷歌的不可用性,最终有助于减轻印度经济的负担。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Depth Distortion Score Estimation in 3-D Image Retargeting using Disparity Map
Depth distortion in an image yields some geometric errors which leads certain image quality degradation. Therefore, it is important to enhance the depth information in the left as well as right stereo images and achieve them in a substantial way. The Disparity Map Acquisition (DMA) algorithm gives rise to the depth distortion with improved disparity matrix. In this paper, we emphasis on depth score enhancement in 3D stereo images retargeting to accomplish the acceptable 3D images with improved depth distortion score. The experimental results show the stereo seam carving which deconsideres the unwanted image patches in order to generate an acceptable 3D stereo images. The obtained 3D stereo images are widely used in the applications of 3D animated movies by abolishing the blurriness in the stereo images and generate the images where the users can relish with the better visual effects. This may lead to the non-usability of 3D sterilize googles and eventually helps and reduces the burden on Indian economy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Oral Disease Detection using Neural Network A Review on Effectiveness of Artificial Intelligence Techniques in the Detection of COVID-19 Accident Avoidance Simulation using SUMO Gesture-Based Model of Mixed Reality Human-Computer Interface The Survey of Digital Image Analysis with Artificial Intelligence- DCNN Technique
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1