{"title":"三角网格的顶点数据压缩","authors":"Eung-Seok Lee, Hyeongseok Ko","doi":"10.1109/PCCGA.2000.883945","DOIUrl":null,"url":null,"abstract":"In the field of geometry compression, two main compression targets exist. One is triangle connectivity data and the other is vertex position data. The authors propose a novel algorithm to compress the vertex data. A fundamentally different approach taken in the paper is to transform the vertex positions to the model space, a coordinate system formed by the three previously processed vertices. Once all the vertices are transformed, we found that the result shows a strong tendency to cluster around three points. We exploit such a tendency during the vector quantization steps to increase the compression ratio. According to the experiments performed on 12 models, the average compression performance of our algorithm is 6.7 bits/vertex, which is a clear improvement over previous methods.","PeriodicalId":342067,"journal":{"name":"Proceedings the Eighth Pacific Conference on Computer Graphics and Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"62","resultStr":"{\"title\":\"Vertex data compression for triangular meshes\",\"authors\":\"Eung-Seok Lee, Hyeongseok Ko\",\"doi\":\"10.1109/PCCGA.2000.883945\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the field of geometry compression, two main compression targets exist. One is triangle connectivity data and the other is vertex position data. The authors propose a novel algorithm to compress the vertex data. A fundamentally different approach taken in the paper is to transform the vertex positions to the model space, a coordinate system formed by the three previously processed vertices. Once all the vertices are transformed, we found that the result shows a strong tendency to cluster around three points. We exploit such a tendency during the vector quantization steps to increase the compression ratio. According to the experiments performed on 12 models, the average compression performance of our algorithm is 6.7 bits/vertex, which is a clear improvement over previous methods.\",\"PeriodicalId\":342067,\"journal\":{\"name\":\"Proceedings the Eighth Pacific Conference on Computer Graphics and Applications\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"62\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings the Eighth Pacific Conference on Computer Graphics and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PCCGA.2000.883945\",\"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 the Eighth Pacific Conference on Computer Graphics and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCCGA.2000.883945","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In the field of geometry compression, two main compression targets exist. One is triangle connectivity data and the other is vertex position data. The authors propose a novel algorithm to compress the vertex data. A fundamentally different approach taken in the paper is to transform the vertex positions to the model space, a coordinate system formed by the three previously processed vertices. Once all the vertices are transformed, we found that the result shows a strong tendency to cluster around three points. We exploit such a tendency during the vector quantization steps to increase the compression ratio. According to the experiments performed on 12 models, the average compression performance of our algorithm is 6.7 bits/vertex, which is a clear improvement over previous methods.