{"title":"基于特征点检测的目标深度测量","authors":"Lai Yufeng, Wang Zhongsheng","doi":"10.2991/pntim-19.2019.66","DOIUrl":null,"url":null,"abstract":"In order to simplify the method of obtaining absolute depth information, this paper proposes a method of automatic measurement of object depth information in images by monocular camera without calibration and adjustment of camera parameters, which is used to realize an automatic depth measurement system. This method uses the feature points on the object image to measure the depth of the object to enhance the robustness of the algorithm against partial occlusion or missing of the measured object in the scene. Experimental results show that the method is effective. Keywords-Component; Feature Points; Absolute Depth; Image Segmentation; the Object Matching","PeriodicalId":344913,"journal":{"name":"Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)","volume":"2022 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Object Depth Measurement Based on Feature Point Detection\",\"authors\":\"Lai Yufeng, Wang Zhongsheng\",\"doi\":\"10.2991/pntim-19.2019.66\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to simplify the method of obtaining absolute depth information, this paper proposes a method of automatic measurement of object depth information in images by monocular camera without calibration and adjustment of camera parameters, which is used to realize an automatic depth measurement system. This method uses the feature points on the object image to measure the depth of the object to enhance the robustness of the algorithm against partial occlusion or missing of the measured object in the scene. Experimental results show that the method is effective. Keywords-Component; Feature Points; Absolute Depth; Image Segmentation; the Object Matching\",\"PeriodicalId\":344913,\"journal\":{\"name\":\"Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)\",\"volume\":\"2022 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/pntim-19.2019.66\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/pntim-19.2019.66","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Object Depth Measurement Based on Feature Point Detection
In order to simplify the method of obtaining absolute depth information, this paper proposes a method of automatic measurement of object depth information in images by monocular camera without calibration and adjustment of camera parameters, which is used to realize an automatic depth measurement system. This method uses the feature points on the object image to measure the depth of the object to enhance the robustness of the algorithm against partial occlusion or missing of the measured object in the scene. Experimental results show that the method is effective. Keywords-Component; Feature Points; Absolute Depth; Image Segmentation; the Object Matching