Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time
Gestures are an important aspect of human interaction and also in the context of human computer interaction. Gesture recognition is the mathematical interpretation of a human motion by a computing device. It is often used hand or head gestures for input commands in personal computers. By recognizing...
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| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/10586/1/Finger%20Application%20Using%20K-Curvature%20Methods%20and%20Kinect%20Sensor%20in%20Real-time.pdf http://umpir.ump.edu.my/id/eprint/10586/ |
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| Summary: | Gestures are an important aspect of human interaction and also in the context of human computer interaction. Gesture recognition is the mathematical interpretation of a human motion by a computing device. It is often used hand or head gestures for input commands in personal computers. By recognizing the hand gesture as input, it allows the user access the computer interactively and makes interaction
more natural. This paper presents a finger detection application by using Kinect. Kinect is a depth sensor is that is an effective device to capture the gesture in real-time. To detect and recognize the fingertips, it needs to extract the detail of the captured hand image using image processing methods. İn this paper, the proposed method is to detect and recognizes the fingertips by using the K-Curvature algorithm. Finally, the finger counting application is applied and the proposed method is discussed at the end of this paper. The results obtained from the
experiment show that the average accuracy for the fingertips
detection is 73.7% and the average processing time is 15.73 ms. |
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