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Robust human computer interaction using dynamic hand gesture recognition
| Content Provider | Semantic Scholar |
|---|---|
| Author | Yang, Shuai |
| Copyright Year | 2016 |
| Abstract | Hand gesture recognition has been applied to many fields in recent years, especially in man-machine interaction (MMI) area, which is regarded as a more natural and flexible input than the traditional input, such as, mice and keyboard. Microsoft Kinect camera has also drastically changed the world of human computer interaction based computer vision, due to its low cost and high quality of depth information for visual images. This has made the depth data to become common place at a very low cost allowing myriad of computer vision related applications including hand gesture recognition. Hand gesture recognition research suffered severely from the clutter and skintone regions in any background. With the availability of depth information, background clutter and skintone regions which are not part of the hand gesture can be removed improving the performance of any classification strategy. In this thesis, an overview of hand gesture recognition research up to date is presented, which includes common stages of hand gesture recognition, common methods and technique of each stage, the state of the recent research and summaries of some successful hand gesture recognition models. This article also discusses a novel hand detection strategy based on Kinect camera by combining depth and colour image information. In the detection procedure, the Kalman filter is applied to tracking process to achieve a good detection result. The experiment results in chapter 3 show this detection method is reliable and |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ro.uow.edu.au/cgi/viewcontent.cgi?article=5792&context=theses |
| Alternate Webpage(s) | https://ro.uow.edu.au/cgi/viewcontent.cgi?article=5792&context=theses&httpsredir=1&referer= |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
