M. A. Qureshi, Abdul Aziz, M. A. Saeed, M. Hayat, Jam Shahid Rasool
{"title":"一种高效的人类手势识别算法的实现","authors":"M. A. Qureshi, Abdul Aziz, M. A. Saeed, M. Hayat, Jam Shahid Rasool","doi":"10.1109/SIECPC.2011.5876948","DOIUrl":null,"url":null,"abstract":"This paper is aimed to help Disabled Persons to do their daily routine work without seeking assistance from others. It works in the domain of Humans Computer Interaction (HCI) and image processing, which are key areas of research in computer history. System developers have used different ways to interact with the computer. Hand gestures are very popular because there are number of different gestures that can be use to achieve different tasks and can also be use to communicate with computer systems. Detection of a hand gesture in a real time environment is a critical task where time and memory are important issues. The systems consists of two parts one is the detection of the performed gesture from the live feed, while the other is taking decision on the basis of detected gestures with the help of control hardware. Solution suggested by us has the ability to detect large number of gestures; it is also very intelligent and can be made to learn gestures at run time for user support.","PeriodicalId":125634,"journal":{"name":"2011 Saudi International Electronics, Communications and Photonics Conference (SIECPC)","volume":"315 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Implementation of an efficient algorithm for Human hand gesture identification\",\"authors\":\"M. A. Qureshi, Abdul Aziz, M. A. Saeed, M. Hayat, Jam Shahid Rasool\",\"doi\":\"10.1109/SIECPC.2011.5876948\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is aimed to help Disabled Persons to do their daily routine work without seeking assistance from others. It works in the domain of Humans Computer Interaction (HCI) and image processing, which are key areas of research in computer history. System developers have used different ways to interact with the computer. Hand gestures are very popular because there are number of different gestures that can be use to achieve different tasks and can also be use to communicate with computer systems. Detection of a hand gesture in a real time environment is a critical task where time and memory are important issues. The systems consists of two parts one is the detection of the performed gesture from the live feed, while the other is taking decision on the basis of detected gestures with the help of control hardware. Solution suggested by us has the ability to detect large number of gestures; it is also very intelligent and can be made to learn gestures at run time for user support.\",\"PeriodicalId\":125634,\"journal\":{\"name\":\"2011 Saudi International Electronics, Communications and Photonics Conference (SIECPC)\",\"volume\":\"315 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Saudi International Electronics, Communications and Photonics Conference (SIECPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIECPC.2011.5876948\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Saudi International Electronics, Communications and Photonics Conference (SIECPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIECPC.2011.5876948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of an efficient algorithm for Human hand gesture identification
This paper is aimed to help Disabled Persons to do their daily routine work without seeking assistance from others. It works in the domain of Humans Computer Interaction (HCI) and image processing, which are key areas of research in computer history. System developers have used different ways to interact with the computer. Hand gestures are very popular because there are number of different gestures that can be use to achieve different tasks and can also be use to communicate with computer systems. Detection of a hand gesture in a real time environment is a critical task where time and memory are important issues. The systems consists of two parts one is the detection of the performed gesture from the live feed, while the other is taking decision on the basis of detected gestures with the help of control hardware. Solution suggested by us has the ability to detect large number of gestures; it is also very intelligent and can be made to learn gestures at run time for user support.