{"title":"android智能手机上的实时视频处理和目标检测","authors":"S. Chaudhari, S. Patil","doi":"10.1109/EESCO.2015.7254003","DOIUrl":null,"url":null,"abstract":"As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; understanding of images. For mobile computer vision, Smartphone must be faster and real time. In this study two applications have been developed on Android platform using OpenCV and core library called as CamTest with own implemented algorithms. Efficiency of two Android applications have been compared and found that OpenCV performs faster than CamTest. The results of examining the best object detection algorithm with reverence to efficiency shows that FAST algorithm has the finest blend of speed and object detection performance. Next projected object recognition system using FAST algorithm, which uses SVM, BPNN for training and validation of object in real time. The application detects the object perfectly with recognition time around 2 ms using SVM and 1 ms using BPNN.","PeriodicalId":305584,"journal":{"name":"2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)","volume":"119 10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Real time video processing and object detection on android smartphone\",\"authors\":\"S. Chaudhari, S. Patil\",\"doi\":\"10.1109/EESCO.2015.7254003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; understanding of images. For mobile computer vision, Smartphone must be faster and real time. In this study two applications have been developed on Android platform using OpenCV and core library called as CamTest with own implemented algorithms. Efficiency of two Android applications have been compared and found that OpenCV performs faster than CamTest. The results of examining the best object detection algorithm with reverence to efficiency shows that FAST algorithm has the finest blend of speed and object detection performance. Next projected object recognition system using FAST algorithm, which uses SVM, BPNN for training and validation of object in real time. The application detects the object perfectly with recognition time around 2 ms using SVM and 1 ms using BPNN.\",\"PeriodicalId\":305584,\"journal\":{\"name\":\"2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)\",\"volume\":\"119 10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EESCO.2015.7254003\",\"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 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EESCO.2015.7254003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real time video processing and object detection on android smartphone
As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; understanding of images. For mobile computer vision, Smartphone must be faster and real time. In this study two applications have been developed on Android platform using OpenCV and core library called as CamTest with own implemented algorithms. Efficiency of two Android applications have been compared and found that OpenCV performs faster than CamTest. The results of examining the best object detection algorithm with reverence to efficiency shows that FAST algorithm has the finest blend of speed and object detection performance. Next projected object recognition system using FAST algorithm, which uses SVM, BPNN for training and validation of object in real time. The application detects the object perfectly with recognition time around 2 ms using SVM and 1 ms using BPNN.