Door detection in images of 3D scenes in an electronic travel aid for the blind

P. Skulimowski, Mateusz Owczarek, P. Strumiłło
{"title":"Door detection in images of 3D scenes in an electronic travel aid for the blind","authors":"P. Skulimowski, Mateusz Owczarek, P. Strumiłło","doi":"10.1109/ISPA.2017.8073593","DOIUrl":null,"url":null,"abstract":"In this paper we propose a fast method for detecting doors in images of 3D scenes. First, the equation estimating the orientation and location of the ground surface is computed. This information is used in further processing steps of the algorithm. Then, the edge image is calculated (using the Canny edge detector) and line segments justifying predefined conditions are searched for by applying the Probabilistic Hough Transform method. Pairs of parallel line segments perpendicular to the ground surface located at a distance range 80–110 cm are identified. The detection performance has been also enhanced by detecting door handles. The proposed method was successfully verified on the recorded indoor RGB-D video sequences acquired by a vision based Electronic Travel Aid (ETA) for the blind. The achieved door detection performance for the tested sequences is at a level of 63% for sensitivity and 84% for positive predictivity values.","PeriodicalId":117602,"journal":{"name":"Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2017.8073593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

In this paper we propose a fast method for detecting doors in images of 3D scenes. First, the equation estimating the orientation and location of the ground surface is computed. This information is used in further processing steps of the algorithm. Then, the edge image is calculated (using the Canny edge detector) and line segments justifying predefined conditions are searched for by applying the Probabilistic Hough Transform method. Pairs of parallel line segments perpendicular to the ground surface located at a distance range 80–110 cm are identified. The detection performance has been also enhanced by detecting door handles. The proposed method was successfully verified on the recorded indoor RGB-D video sequences acquired by a vision based Electronic Travel Aid (ETA) for the blind. The achieved door detection performance for the tested sequences is at a level of 63% for sensitivity and 84% for positive predictivity values.
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
盲人电子旅行辅助设备三维场景图像中的门检测
本文提出了一种快速检测三维场景图像中的门的方法。首先,计算了地表方位和位置的估计方程。该信息用于算法的进一步处理步骤。然后,计算边缘图像(使用Canny边缘检测器),并通过应用概率霍夫变换方法搜索证明预定义条件的线段。在80-110 cm的距离范围内确定了垂直于地面的平行线段对。检测门把手也提高了检测性能。利用基于视觉的盲人电子旅行辅助系统(ETA)采集的室内RGB-D视频序列,成功验证了该方法的有效性。测试序列的门检测性能达到63%的灵敏度和84%的阳性预测值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Robust real-time chest compression rate detection from smartphone video Image registration with subpixel accuracy of DCT-sign phase correlation with real subpixel shifted images Choosing an accurate number of mel frequency cepstral coefficients for audio classification purpose Blind determination of quality of JPEG compressed images Differentiating ureter and arteries in the pelvic via endoscope using deep neural network
×
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