{"title":"先进的低成本集群系统","authors":"G. Spampinato, A. Bruna, S. Curti, Viviana D'Alto","doi":"10.1109/IPTA.2016.7821015","DOIUrl":null,"url":null,"abstract":"This document describes a system to gather information from a stationary camera to identify moving objects. The proposed solution makes only use of motion vectors between adjacent frames, obtained from any algorithm. Starting from them, the system is able to retrieve clusters of moving objects in a scene acquired by an image sensor device. Since all the system is only based on optical flow, it is really simple and fast, to be easily integrated directly in low cost cameras. The experimental results show fast and robust performance of our method. The computation time is about 800 frame/sec for a VGA sequence on a 2.3GHz processor (ARM Cortex-A15). Moreover, the system has been tested for different applications, cross traffic alert and video surveillance, in different conditions, indoor and outdoor, and with different lens, linear and fish-eye.","PeriodicalId":123429,"journal":{"name":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Advanced low cost clustering system\",\"authors\":\"G. Spampinato, A. Bruna, S. Curti, Viviana D'Alto\",\"doi\":\"10.1109/IPTA.2016.7821015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This document describes a system to gather information from a stationary camera to identify moving objects. The proposed solution makes only use of motion vectors between adjacent frames, obtained from any algorithm. Starting from them, the system is able to retrieve clusters of moving objects in a scene acquired by an image sensor device. Since all the system is only based on optical flow, it is really simple and fast, to be easily integrated directly in low cost cameras. The experimental results show fast and robust performance of our method. The computation time is about 800 frame/sec for a VGA sequence on a 2.3GHz processor (ARM Cortex-A15). Moreover, the system has been tested for different applications, cross traffic alert and video surveillance, in different conditions, indoor and outdoor, and with different lens, linear and fish-eye.\",\"PeriodicalId\":123429,\"journal\":{\"name\":\"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTA.2016.7821015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2016.7821015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This document describes a system to gather information from a stationary camera to identify moving objects. The proposed solution makes only use of motion vectors between adjacent frames, obtained from any algorithm. Starting from them, the system is able to retrieve clusters of moving objects in a scene acquired by an image sensor device. Since all the system is only based on optical flow, it is really simple and fast, to be easily integrated directly in low cost cameras. The experimental results show fast and robust performance of our method. The computation time is about 800 frame/sec for a VGA sequence on a 2.3GHz processor (ARM Cortex-A15). Moreover, the system has been tested for different applications, cross traffic alert and video surveillance, in different conditions, indoor and outdoor, and with different lens, linear and fish-eye.