{"title":"三维模型检索的特征组合与相关反馈","authors":"I. Atmosukarto, W. Leow, Zhiyong Huang","doi":"10.1109/MMMC.2005.39","DOIUrl":null,"url":null,"abstract":"Retrieval of 3D models have attracted much research interest, and many types of shape features have been proposed. In this paper, we describe a novel approach of combining the feature types for 3D model retrieval and relevance feedback processing.Our approach performs query processing using pre-computed pairwise distances between objects measured according to various feature types. Experimental tests show that this approach performs better than retrieval by individual feature type.","PeriodicalId":121228,"journal":{"name":"11th International Multimedia Modelling Conference","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"61","resultStr":"{\"title\":\"Feature Combination and Relevance Feedback for 3D Model Retrieval\",\"authors\":\"I. Atmosukarto, W. Leow, Zhiyong Huang\",\"doi\":\"10.1109/MMMC.2005.39\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Retrieval of 3D models have attracted much research interest, and many types of shape features have been proposed. In this paper, we describe a novel approach of combining the feature types for 3D model retrieval and relevance feedback processing.Our approach performs query processing using pre-computed pairwise distances between objects measured according to various feature types. Experimental tests show that this approach performs better than retrieval by individual feature type.\",\"PeriodicalId\":121228,\"journal\":{\"name\":\"11th International Multimedia Modelling Conference\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-01-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"61\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"11th International Multimedia Modelling Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMMC.2005.39\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"11th International Multimedia Modelling Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMMC.2005.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature Combination and Relevance Feedback for 3D Model Retrieval
Retrieval of 3D models have attracted much research interest, and many types of shape features have been proposed. In this paper, we describe a novel approach of combining the feature types for 3D model retrieval and relevance feedback processing.Our approach performs query processing using pre-computed pairwise distances between objects measured according to various feature types. Experimental tests show that this approach performs better than retrieval by individual feature type.