{"title":"基于CNN的立体视觉算法鲁棒性研究","authors":"A. Zanela, S. Taraglio","doi":"10.1109/CNNA.1998.685395","DOIUrl":null,"url":null,"abstract":"The development of an effective system for autonomous robot navigation can find a valid support from the CNN approach. In the paper some measurements of the robustness of a stereo vision algorithm based on the CNN paradigm are presented. The sensitivity of the algorithm to the difference in luminosity and contrast of the images in the stereo pair, the presence of noise corrupting the images and problems of misalignment in the experimental set-up are investigated.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A robustness study of a CNN based stereo vision algorithm\",\"authors\":\"A. Zanela, S. Taraglio\",\"doi\":\"10.1109/CNNA.1998.685395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of an effective system for autonomous robot navigation can find a valid support from the CNN approach. In the paper some measurements of the robustness of a stereo vision algorithm based on the CNN paradigm are presented. The sensitivity of the algorithm to the difference in luminosity and contrast of the images in the stereo pair, the presence of noise corrupting the images and problems of misalignment in the experimental set-up are investigated.\",\"PeriodicalId\":171485,\"journal\":{\"name\":\"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)\",\"volume\":\"150 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CNNA.1998.685395\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNNA.1998.685395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A robustness study of a CNN based stereo vision algorithm
The development of an effective system for autonomous robot navigation can find a valid support from the CNN approach. In the paper some measurements of the robustness of a stereo vision algorithm based on the CNN paradigm are presented. The sensitivity of the algorithm to the difference in luminosity and contrast of the images in the stereo pair, the presence of noise corrupting the images and problems of misalignment in the experimental set-up are investigated.