{"title":"Android移动设备上粒子滤波算法的并行实现","authors":"Alejandro Acosta, F. Almeida","doi":"10.1109/PDP.2015.93","DOIUrl":null,"url":null,"abstract":"The advent of emergent System-on-Chip (SoCs) and multiprocessor System-on-Chip (MPSocs) opens a new era on the small mobile devices (Smartphones, Tablets, ) in terms of computing capabilities and applications to be addressed. Given the ability of these devices to interact with the real world through the camera, is mandatory the development of efficient algorithms related to image processing and computer vision. We present a parallel implementation on mobile Android devices of the Particle Filter algorithm. We developed three different version of this algorithm. A Java sequential implementation and two Render script parallel versions, an ad-hoc implementation and a Paralldroid generated implementation. The results obtained by the parallel versions present an important speedup and a high accurate with a high processing rate of frame per seconds.","PeriodicalId":285111,"journal":{"name":"2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Parallel Implementations of the Particle Filter Algorithm for Android Mobile Devices\",\"authors\":\"Alejandro Acosta, F. Almeida\",\"doi\":\"10.1109/PDP.2015.93\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The advent of emergent System-on-Chip (SoCs) and multiprocessor System-on-Chip (MPSocs) opens a new era on the small mobile devices (Smartphones, Tablets, ) in terms of computing capabilities and applications to be addressed. Given the ability of these devices to interact with the real world through the camera, is mandatory the development of efficient algorithms related to image processing and computer vision. We present a parallel implementation on mobile Android devices of the Particle Filter algorithm. We developed three different version of this algorithm. A Java sequential implementation and two Render script parallel versions, an ad-hoc implementation and a Paralldroid generated implementation. The results obtained by the parallel versions present an important speedup and a high accurate with a high processing rate of frame per seconds.\",\"PeriodicalId\":285111,\"journal\":{\"name\":\"2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PDP.2015.93\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDP.2015.93","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallel Implementations of the Particle Filter Algorithm for Android Mobile Devices
The advent of emergent System-on-Chip (SoCs) and multiprocessor System-on-Chip (MPSocs) opens a new era on the small mobile devices (Smartphones, Tablets, ) in terms of computing capabilities and applications to be addressed. Given the ability of these devices to interact with the real world through the camera, is mandatory the development of efficient algorithms related to image processing and computer vision. We present a parallel implementation on mobile Android devices of the Particle Filter algorithm. We developed three different version of this algorithm. A Java sequential implementation and two Render script parallel versions, an ad-hoc implementation and a Paralldroid generated implementation. The results obtained by the parallel versions present an important speedup and a high accurate with a high processing rate of frame per seconds.