{"title":"使用泛倾斜变焦系统的目标视频跟踪","authors":"Mohammed A. Taha, Sharief F. Babiker","doi":"10.53332/kuej.v4i1.1041","DOIUrl":null,"url":null,"abstract":"This paper implements object video tracking system that represents object location in subsequent video frames. A closed-circuit television (CCTV) camera mounted on a rotating system is used for capturing video while the object of interest always kept at the centre of the screen. Three tracking algorithms were selected and implemented: template matching, contour matching and optical flow. Measures of their accuracy and speed were taken for comparison. The software was implemented in a personal computer with C# programming language, with the aid of EmguCV which is a wrapper for OpenCV, a famous image processing library. The system implemented for this study is able to successfully track a rigid body, discernible from the background objects with size up to 400×300 pixel for the Phase Alternate Line (PAL) system of 720×576 pixel frame size. Tracking was stable even with the existence of rotation and scaling. Some faults were observed when occlusion was present or when the target was moving with a speed faster than that of the rotation system of 30 degrees/s horizontal and 15 degrees/s vertical.","PeriodicalId":23461,"journal":{"name":"University of Khartoum Engineering Journal","volume":"6 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Object Video Tracking using a Pan-Tilt-Zoom System\",\"authors\":\"Mohammed A. Taha, Sharief F. Babiker\",\"doi\":\"10.53332/kuej.v4i1.1041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper implements object video tracking system that represents object location in subsequent video frames. A closed-circuit television (CCTV) camera mounted on a rotating system is used for capturing video while the object of interest always kept at the centre of the screen. Three tracking algorithms were selected and implemented: template matching, contour matching and optical flow. Measures of their accuracy and speed were taken for comparison. The software was implemented in a personal computer with C# programming language, with the aid of EmguCV which is a wrapper for OpenCV, a famous image processing library. The system implemented for this study is able to successfully track a rigid body, discernible from the background objects with size up to 400×300 pixel for the Phase Alternate Line (PAL) system of 720×576 pixel frame size. Tracking was stable even with the existence of rotation and scaling. Some faults were observed when occlusion was present or when the target was moving with a speed faster than that of the rotation system of 30 degrees/s horizontal and 15 degrees/s vertical.\",\"PeriodicalId\":23461,\"journal\":{\"name\":\"University of Khartoum Engineering Journal\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"University of Khartoum Engineering Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53332/kuej.v4i1.1041\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"University of Khartoum Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53332/kuej.v4i1.1041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Object Video Tracking using a Pan-Tilt-Zoom System
This paper implements object video tracking system that represents object location in subsequent video frames. A closed-circuit television (CCTV) camera mounted on a rotating system is used for capturing video while the object of interest always kept at the centre of the screen. Three tracking algorithms were selected and implemented: template matching, contour matching and optical flow. Measures of their accuracy and speed were taken for comparison. The software was implemented in a personal computer with C# programming language, with the aid of EmguCV which is a wrapper for OpenCV, a famous image processing library. The system implemented for this study is able to successfully track a rigid body, discernible from the background objects with size up to 400×300 pixel for the Phase Alternate Line (PAL) system of 720×576 pixel frame size. Tracking was stable even with the existence of rotation and scaling. Some faults were observed when occlusion was present or when the target was moving with a speed faster than that of the rotation system of 30 degrees/s horizontal and 15 degrees/s vertical.