{"title":"Cloud based multimedia analytic platform","authors":"Peng Wu, R. Vernica, Qian Lin","doi":"10.1145/2502081.2502254","DOIUrl":null,"url":null,"abstract":"Multimedia Analytic Platform is a cloud based service to expose state-of-the-art multimedia technologies for mobile and web application development. As a product-quality service platform, it offers comprehensive API documentation, code example, service description and sandbox for trial for each multimedia technology. The utilization of the cloud storage and distributed computing framework allows the service platform to run with robustness and efficiency. The current technologies supported by the platform include face detection, face verification, face demographic estimation, feature extraction, image matching, and image collage. Since its initial public launch in October 2012, it has been adopted by universities and third party companies for course support and application development.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 21st ACM international conference on Multimedia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2502081.2502254","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Multimedia Analytic Platform is a cloud based service to expose state-of-the-art multimedia technologies for mobile and web application development. As a product-quality service platform, it offers comprehensive API documentation, code example, service description and sandbox for trial for each multimedia technology. The utilization of the cloud storage and distributed computing framework allows the service platform to run with robustness and efficiency. The current technologies supported by the platform include face detection, face verification, face demographic estimation, feature extraction, image matching, and image collage. Since its initial public launch in October 2012, it has been adopted by universities and third party companies for course support and application development.
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