{"title":"运动训练目标图像快速检索算法研究","authors":"Jun Guo, Xiaoyu Wu","doi":"10.1109/2ICML58251.2022.00014","DOIUrl":null,"url":null,"abstract":"Current traditional image retrieval methods achieve image retrieval by matching a single feature of an image, which leads to poor retrieval results due to the lack of pre-processing of the image. In this regard, the work proposes a study of a fast retrieval algorithm for sports training target images. By extracting visual features of sports training target images and generating corresponding visual vocabulary, denoising and visually enhancing the images, fast image retrieval is achieved by calculating image similarity measures. In the experiments, the proposed retrieval method is verified for retrieval performance. The experimental analysis shows that the proposed method has high retrieval speed and accuracy in retrieving images, and has a good overall retrieval performance.","PeriodicalId":355485,"journal":{"name":"2022 International Conference on Intelligent Computing and Machine Learning (2ICML)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Fast Retrieval Algorithm for Sports Training Target Images\",\"authors\":\"Jun Guo, Xiaoyu Wu\",\"doi\":\"10.1109/2ICML58251.2022.00014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Current traditional image retrieval methods achieve image retrieval by matching a single feature of an image, which leads to poor retrieval results due to the lack of pre-processing of the image. In this regard, the work proposes a study of a fast retrieval algorithm for sports training target images. By extracting visual features of sports training target images and generating corresponding visual vocabulary, denoising and visually enhancing the images, fast image retrieval is achieved by calculating image similarity measures. In the experiments, the proposed retrieval method is verified for retrieval performance. The experimental analysis shows that the proposed method has high retrieval speed and accuracy in retrieving images, and has a good overall retrieval performance.\",\"PeriodicalId\":355485,\"journal\":{\"name\":\"2022 International Conference on Intelligent Computing and Machine Learning (2ICML)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Intelligent Computing and Machine Learning (2ICML)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/2ICML58251.2022.00014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Intelligent Computing and Machine Learning (2ICML)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/2ICML58251.2022.00014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Fast Retrieval Algorithm for Sports Training Target Images
Current traditional image retrieval methods achieve image retrieval by matching a single feature of an image, which leads to poor retrieval results due to the lack of pre-processing of the image. In this regard, the work proposes a study of a fast retrieval algorithm for sports training target images. By extracting visual features of sports training target images and generating corresponding visual vocabulary, denoising and visually enhancing the images, fast image retrieval is achieved by calculating image similarity measures. In the experiments, the proposed retrieval method is verified for retrieval performance. The experimental analysis shows that the proposed method has high retrieval speed and accuracy in retrieving images, and has a good overall retrieval performance.