{"title":"基于GPU的空间划分几何哈希","authors":"Bhavin Patel, Vibha Patel","doi":"10.1109/IC3.2014.6897170","DOIUrl":null,"url":null,"abstract":"This paper presents a Graphics Processing Unit (GPU) based solution for classical geometric hashing and its variation with transformation functions on Speeded Up Robust Features (SURF) space of images. GPU based classical geometric hashing provides speed-up of 14.0x to 61.0x for offline indexing and 1.08x to 10.06x for online searching compared to sequential one for different partitioning sizes. GPU based transformation by mean invariancy and principal component based alignment with geometric hashing provides speed-up of 12.12x to 63.13x for offline indexing and 1.02x to 5.82x for online searching. This paper also proposes solution to execute multiple query simultaneously. It proves to be better than the serial execution of multiple queries. GPU based implementation of multi-query provide speed-up of 1.68x to 460.45x than the sequential one for online searching for multiple queries between 1 to 10 simultaneously. Experimentation is done using standard CASIA Palm-print based images.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GPU based geometric hashing for space partioning\",\"authors\":\"Bhavin Patel, Vibha Patel\",\"doi\":\"10.1109/IC3.2014.6897170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a Graphics Processing Unit (GPU) based solution for classical geometric hashing and its variation with transformation functions on Speeded Up Robust Features (SURF) space of images. GPU based classical geometric hashing provides speed-up of 14.0x to 61.0x for offline indexing and 1.08x to 10.06x for online searching compared to sequential one for different partitioning sizes. GPU based transformation by mean invariancy and principal component based alignment with geometric hashing provides speed-up of 12.12x to 63.13x for offline indexing and 1.02x to 5.82x for online searching. This paper also proposes solution to execute multiple query simultaneously. It proves to be better than the serial execution of multiple queries. GPU based implementation of multi-query provide speed-up of 1.68x to 460.45x than the sequential one for online searching for multiple queries between 1 to 10 simultaneously. Experimentation is done using standard CASIA Palm-print based images.\",\"PeriodicalId\":444918,\"journal\":{\"name\":\"2014 Seventh International Conference on Contemporary Computing (IC3)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Seventh International Conference on Contemporary Computing (IC3)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC3.2014.6897170\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Seventh International Conference on Contemporary Computing (IC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3.2014.6897170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a Graphics Processing Unit (GPU) based solution for classical geometric hashing and its variation with transformation functions on Speeded Up Robust Features (SURF) space of images. GPU based classical geometric hashing provides speed-up of 14.0x to 61.0x for offline indexing and 1.08x to 10.06x for online searching compared to sequential one for different partitioning sizes. GPU based transformation by mean invariancy and principal component based alignment with geometric hashing provides speed-up of 12.12x to 63.13x for offline indexing and 1.02x to 5.82x for online searching. This paper also proposes solution to execute multiple query simultaneously. It proves to be better than the serial execution of multiple queries. GPU based implementation of multi-query provide speed-up of 1.68x to 460.45x than the sequential one for online searching for multiple queries between 1 to 10 simultaneously. Experimentation is done using standard CASIA Palm-print based images.
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