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...
| Main Authors: | , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/10586/ http://umpir.ump.edu.my/id/eprint/10586/1/Finger%20Application%20Using%20K-Curvature%20Methods%20and%20Kinect%20Sensor%20in%20Real-time.pdf |
| id |
ump-10586 |
|---|---|
| recordtype |
eprints |
| spelling |
ump-105862018-04-11T01:44:52Z http://umpir.ump.edu.my/id/eprint/10586/ Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time MM. Zabri, Abu Bakar Rosdiyana, Samad Pebrianti, Dwi Mahfuzah, Mustafa Nor Rul Hasma, Abdullah TK Electrical engineering. Electronics Nuclear engineering 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. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/10586/1/Finger%20Application%20Using%20K-Curvature%20Methods%20and%20Kinect%20Sensor%20in%20Real-time.pdf MM. Zabri, Abu Bakar and Rosdiyana, Samad and Pebrianti, Dwi and Mahfuzah, Mustafa and Nor Rul Hasma, Abdullah (2015) Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time. In: International Symposium on Technology Management and Emerging Technologies, 25-27 August 2014 , Langkawi, Kedah. . (Unpublished) |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Malaysia Pahang |
| building |
UMP Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
TK Electrical engineering. Electronics Nuclear engineering |
| spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering MM. Zabri, Abu Bakar Rosdiyana, Samad Pebrianti, Dwi Mahfuzah, Mustafa Nor Rul Hasma, Abdullah Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time |
| description |
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. |
| format |
Conference or Workshop Item |
| author |
MM. Zabri, Abu Bakar Rosdiyana, Samad Pebrianti, Dwi Mahfuzah, Mustafa Nor Rul Hasma, Abdullah |
| author_facet |
MM. Zabri, Abu Bakar Rosdiyana, Samad Pebrianti, Dwi Mahfuzah, Mustafa Nor Rul Hasma, Abdullah |
| author_sort |
MM. Zabri, Abu Bakar |
| title |
Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time |
| title_short |
Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time |
| title_full |
Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time |
| title_fullStr |
Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time |
| title_full_unstemmed |
Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time |
| title_sort |
finger application using k-curvature methods and kinect sensor in real-time |
| publishDate |
2015 |
| url |
http://umpir.ump.edu.my/id/eprint/10586/ http://umpir.ump.edu.my/id/eprint/10586/1/Finger%20Application%20Using%20K-Curvature%20Methods%20and%20Kinect%20Sensor%20in%20Real-time.pdf |
| first_indexed |
2023-09-18T22:10:21Z |
| last_indexed |
2023-09-18T22:10:21Z |
| _version_ |
1777414985709780992 |