{"title":"Face recognition on mobile platforms","authors":"Kornél Bertók, A. Fazekas","doi":"10.1109/COGINFOCOM.2016.7804521","DOIUrl":null,"url":null,"abstract":"Every year, another generation of smartphones is released that is more capable and stronger than the prior top-class devices. Because of the increased performance and ergonomics of smartphones, the shift away from personal computers is continuously accelerating. Due to this effect, many developers are interested in adapting PC-based solutions to mobile platforms. In this paper, we focus on adapting face recognition algorithms to Android mobile platforms. These algorithms are already part of a Windows desktop application and our aim is to create such an architecture where the application logic has the same source code in different platforms. That is, the article is about a cross-platform development of image processing algorithms. According to our long-term plans, we develop our face recognition algorithms under Windows, but every stable release will be also built as the part of an Android application. In addition, multiple user interfaces must be developed for each platform and we also need interfaces to reach the functionalities of the common application logic from user interfaces. Besides the concept of the architecture and we also quantify the performance of the same algorithms under different platforms.","PeriodicalId":440408,"journal":{"name":"2016 7th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 7th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COGINFOCOM.2016.7804521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Every year, another generation of smartphones is released that is more capable and stronger than the prior top-class devices. Because of the increased performance and ergonomics of smartphones, the shift away from personal computers is continuously accelerating. Due to this effect, many developers are interested in adapting PC-based solutions to mobile platforms. In this paper, we focus on adapting face recognition algorithms to Android mobile platforms. These algorithms are already part of a Windows desktop application and our aim is to create such an architecture where the application logic has the same source code in different platforms. That is, the article is about a cross-platform development of image processing algorithms. According to our long-term plans, we develop our face recognition algorithms under Windows, but every stable release will be also built as the part of an Android application. In addition, multiple user interfaces must be developed for each platform and we also need interfaces to reach the functionalities of the common application logic from user interfaces. Besides the concept of the architecture and we also quantify the performance of the same algorithms under different platforms.