{"title":"OpenIMAJ和ImageTerrier:用于可伸缩多媒体分析和图像索引的Java库和工具","authors":"Jonathon S. Hare, Sina Samangooei, D. Dupplaw","doi":"10.1145/2072298.2072421","DOIUrl":null,"url":null,"abstract":"OpenIMAJ and ImageTerrier are recently released open-source libraries and tools for experimentation and development of multimedia applications using Java-compatible programming languages. OpenIMAJ (the Open toolkit for Intelligent Multimedia Analysis in Java) is a collection of libraries for multimedia analysis. The image libraries contain methods for processing images and extracting state-of-the-art features, including SIFT. The video and audio libraries support both cross-platform capture and processing. The clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering algorithms. The clustering library makes it possible to easily create BoVW representations for images and videos. OpenIMAJ also incorporates a number of tools to enable extremely-large-scale multimedia analysis using distributed computing with Apache Hadoop. ImageTerrier is a scalable, high-performance search engine platform for content-based image retrieval applications using features extracted with the OpenIMAJ library and tools. The ImageTerrier platform provides a comprehensive test-bed for experimenting with image retrieval techniques. The platform incorporates a state-of-the-art implementation of the single-pass indexing technique for constructing inverted indexes and is capable of producing highly compressed index data structures.","PeriodicalId":318758,"journal":{"name":"Proceedings of the 19th ACM international conference on Multimedia","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"82","resultStr":"{\"title\":\"OpenIMAJ and ImageTerrier: Java libraries and tools for scalable multimedia analysis and indexing of images\",\"authors\":\"Jonathon S. Hare, Sina Samangooei, D. Dupplaw\",\"doi\":\"10.1145/2072298.2072421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"OpenIMAJ and ImageTerrier are recently released open-source libraries and tools for experimentation and development of multimedia applications using Java-compatible programming languages. OpenIMAJ (the Open toolkit for Intelligent Multimedia Analysis in Java) is a collection of libraries for multimedia analysis. The image libraries contain methods for processing images and extracting state-of-the-art features, including SIFT. The video and audio libraries support both cross-platform capture and processing. The clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering algorithms. The clustering library makes it possible to easily create BoVW representations for images and videos. OpenIMAJ also incorporates a number of tools to enable extremely-large-scale multimedia analysis using distributed computing with Apache Hadoop. ImageTerrier is a scalable, high-performance search engine platform for content-based image retrieval applications using features extracted with the OpenIMAJ library and tools. The ImageTerrier platform provides a comprehensive test-bed for experimenting with image retrieval techniques. The platform incorporates a state-of-the-art implementation of the single-pass indexing technique for constructing inverted indexes and is capable of producing highly compressed index data structures.\",\"PeriodicalId\":318758,\"journal\":{\"name\":\"Proceedings of the 19th ACM international conference on Multimedia\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"82\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 19th ACM international conference on Multimedia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2072298.2072421\",\"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 of the 19th ACM international conference on Multimedia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2072298.2072421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OpenIMAJ and ImageTerrier: Java libraries and tools for scalable multimedia analysis and indexing of images
OpenIMAJ and ImageTerrier are recently released open-source libraries and tools for experimentation and development of multimedia applications using Java-compatible programming languages. OpenIMAJ (the Open toolkit for Intelligent Multimedia Analysis in Java) is a collection of libraries for multimedia analysis. The image libraries contain methods for processing images and extracting state-of-the-art features, including SIFT. The video and audio libraries support both cross-platform capture and processing. The clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering algorithms. The clustering library makes it possible to easily create BoVW representations for images and videos. OpenIMAJ also incorporates a number of tools to enable extremely-large-scale multimedia analysis using distributed computing with Apache Hadoop. ImageTerrier is a scalable, high-performance search engine platform for content-based image retrieval applications using features extracted with the OpenIMAJ library and tools. The ImageTerrier platform provides a comprehensive test-bed for experimenting with image retrieval techniques. The platform incorporates a state-of-the-art implementation of the single-pass indexing technique for constructing inverted indexes and is capable of producing highly compressed index data structures.