Method for User Interface of Large Displays Using Arm Pointing and Finger Counting Gesture Recognition
Although many three-dimensional pointing gesture recognition methods have been proposed, the problem of self-occlusion has not been considered. Furthermore, because almost all pointing gesture recognition methods use a wide-angle camera, additional sensors or cameras are required to concurrently per...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/683045 |
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| _version_ | 1832545412569890816 |
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| author | Hansol Kim Yoonkyung Kim Eui Chul Lee |
| author_facet | Hansol Kim Yoonkyung Kim Eui Chul Lee |
| author_sort | Hansol Kim |
| collection | DOAJ |
| description | Although many three-dimensional pointing gesture recognition methods have been proposed, the problem of self-occlusion has not been considered. Furthermore, because almost all pointing gesture recognition methods use a wide-angle camera, additional sensors or cameras are required to concurrently perform finger gesture recognition. In this paper, we propose a method for performing both pointing gesture and finger gesture recognition for large display environments, using a single Kinect device and a skeleton tracking model. By considering self-occlusion, a compensation technique can be performed on the user’s detected shoulder position when a hand occludes the shoulder. In addition, we propose a technique to facilitate finger counting gesture recognition, based on the depth image of the hand position. In this technique, the depth image is extracted from the end of the pointing vector. By using exception handling for self-occlusions, experimental results indicate that the pointing accuracy of a specific reference position was significantly improved. The average root mean square error was approximately 13 pixels for a 1920 × 1080 pixels screen resolution. Moreover, the finger counting gesture recognition accuracy was 98.3%. |
| format | Article |
| id | doaj-art-f6ca5a5121a04582afed348b00db18c7 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-f6ca5a5121a04582afed348b00db18c72025-02-03T07:25:54ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/683045683045Method for User Interface of Large Displays Using Arm Pointing and Finger Counting Gesture RecognitionHansol Kim0Yoonkyung Kim1Eui Chul Lee2Department of Computer Science, Sangmyung University, Seoul 110-743, Republic of KoreaDepartment of Computer Science, Sangmyung University, Seoul 110-743, Republic of KoreaDepartment of Computer Science, Sangmyung University, Seoul 110-743, Republic of KoreaAlthough many three-dimensional pointing gesture recognition methods have been proposed, the problem of self-occlusion has not been considered. Furthermore, because almost all pointing gesture recognition methods use a wide-angle camera, additional sensors or cameras are required to concurrently perform finger gesture recognition. In this paper, we propose a method for performing both pointing gesture and finger gesture recognition for large display environments, using a single Kinect device and a skeleton tracking model. By considering self-occlusion, a compensation technique can be performed on the user’s detected shoulder position when a hand occludes the shoulder. In addition, we propose a technique to facilitate finger counting gesture recognition, based on the depth image of the hand position. In this technique, the depth image is extracted from the end of the pointing vector. By using exception handling for self-occlusions, experimental results indicate that the pointing accuracy of a specific reference position was significantly improved. The average root mean square error was approximately 13 pixels for a 1920 × 1080 pixels screen resolution. Moreover, the finger counting gesture recognition accuracy was 98.3%.http://dx.doi.org/10.1155/2014/683045 |
| spellingShingle | Hansol Kim Yoonkyung Kim Eui Chul Lee Method for User Interface of Large Displays Using Arm Pointing and Finger Counting Gesture Recognition The Scientific World Journal |
| title | Method for User Interface of Large Displays Using Arm Pointing and Finger Counting Gesture Recognition |
| title_full | Method for User Interface of Large Displays Using Arm Pointing and Finger Counting Gesture Recognition |
| title_fullStr | Method for User Interface of Large Displays Using Arm Pointing and Finger Counting Gesture Recognition |
| title_full_unstemmed | Method for User Interface of Large Displays Using Arm Pointing and Finger Counting Gesture Recognition |
| title_short | Method for User Interface of Large Displays Using Arm Pointing and Finger Counting Gesture Recognition |
| title_sort | method for user interface of large displays using arm pointing and finger counting gesture recognition |
| url | http://dx.doi.org/10.1155/2014/683045 |
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