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2021 3rd International Conference on Robotics and Computer Vision (ICRCV)最新文献

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SC-PROSAC: An Improved Progressive Sample Consensus Algorithm Based on Spectral Clustering SC-PROSAC:一种改进的基于谱聚类的渐进样本一致性算法
2021 3rd International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2021-08-06 DOI: 10.1109/ICRCV52986.2021.9546964
Shuhua Ma, Xianchun Ma, Hairong You, Tiang Tang, Jinhua Wang, Min Wang
{"title":"SC-PROSAC: An Improved Progressive Sample Consensus Algorithm Based on Spectral Clustering","authors":"Shuhua Ma, Xianchun Ma, Hairong You, Tiang Tang, Jinhua Wang, Min Wang","doi":"10.1109/ICRCV52986.2021.9546964","DOIUrl":"https://doi.org/10.1109/ICRCV52986.2021.9546964","url":null,"abstract":"This paper proposes an improved progressive consensus sampling (PROSAC) algorithm based on the spectral clustering algorithm, which aiming at the problem that the calculation model of PROSAC may fail, resulting in low final matching accuracy. First, the spectral clustering algorithm is used to filter the generated subset of the PROSAC algorithm, and then based on the selected subset, a high-precision calculation model is generated, and finally the final match is obtained according to the calculation model. The experimental results show that the calculation model generated by the improved PROSAC algorithm has high accuracy, thereby improving the accuracy and efficiency of image matching.","PeriodicalId":377887,"journal":{"name":"2021 3rd International Conference on Robotics and Computer Vision (ICRCV)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133141740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Body Motion Detection Technology in Video 视频中的身体运动检测技术
2021 3rd International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2021-08-06 DOI: 10.1109/ICRCV52986.2021.9546980
Lijuan Qin, Zhi-qiang Liu
{"title":"Body Motion Detection Technology in Video","authors":"Lijuan Qin, Zhi-qiang Liu","doi":"10.1109/ICRCV52986.2021.9546980","DOIUrl":"https://doi.org/10.1109/ICRCV52986.2021.9546980","url":null,"abstract":"The detection and recognition of human body movement involves the research direction of multi-disciplinary knowledge, including digital image processing, computer vision and other professional fields. This paper first introduces three common moving object detection algorithms: background subtraction, inter frame difference and optical flow. On the basis of frame difference method and image edge detection algorithm, a dynamic edge point preserving method is proposed to realize moving object detection. This method combines the motion information and edge information of the picture, and can obtain the edge information of moving object in video sequence more accurately, which is more suitable for human body’s body motion detection.","PeriodicalId":377887,"journal":{"name":"2021 3rd International Conference on Robotics and Computer Vision (ICRCV)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132596488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
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