Abstract
Human-machine interaction is a popular research filed recently. Microsoft Kinect can provide us an economical way for tracking the skeleton of the human body. In this study, we present an efficient Kinect-based method for a potential application of TV remote controller. The proposed method consists of two parts: four direction (up/down/left/right) recognition and handwritten digit recognition. The developed recognitions include five main steps: initialization, tracking skeleton, judging the start condition, recording the path, and recognition. We use an intuitive way to start the event and achieve high accurate recognition for the users. We apply the least square method for the four direction recognition and a support vector machine library for the handwritten digit recognition. Experimental results show that the proposed system has great potential on future human-machine development.
| Original language | English |
|---|---|
| Title of host publication | ISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems |
| Pages | 414-419 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2012 |
| Event | 20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012 - Tamsui, New Taipei City, Taiwan Duration: 2012 Nov 4 → 2012 Nov 7 |
Other
| Other | 20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012 |
|---|---|
| Country | Taiwan |
| City | Tamsui, New Taipei City |
| Period | 12/11/4 → 12/11/7 |
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Keywords
- handwritten digit
- Kinect
- pattern recongition
- support vector machine
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Signal Processing
Cite this
A Kinect-based handwritten digit recognition for TV remote controller. / Chu, Tsai Te; Su, Chung Yen.
ISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems. 2012. p. 414-419 6473522.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A Kinect-based handwritten digit recognition for TV remote controller
AU - Chu, Tsai Te
AU - Su, Chung Yen
PY - 2012
Y1 - 2012
N2 - Human-machine interaction is a popular research filed recently. Microsoft Kinect can provide us an economical way for tracking the skeleton of the human body. In this study, we present an efficient Kinect-based method for a potential application of TV remote controller. The proposed method consists of two parts: four direction (up/down/left/right) recognition and handwritten digit recognition. The developed recognitions include five main steps: initialization, tracking skeleton, judging the start condition, recording the path, and recognition. We use an intuitive way to start the event and achieve high accurate recognition for the users. We apply the least square method for the four direction recognition and a support vector machine library for the handwritten digit recognition. Experimental results show that the proposed system has great potential on future human-machine development.
AB - Human-machine interaction is a popular research filed recently. Microsoft Kinect can provide us an economical way for tracking the skeleton of the human body. In this study, we present an efficient Kinect-based method for a potential application of TV remote controller. The proposed method consists of two parts: four direction (up/down/left/right) recognition and handwritten digit recognition. The developed recognitions include five main steps: initialization, tracking skeleton, judging the start condition, recording the path, and recognition. We use an intuitive way to start the event and achieve high accurate recognition for the users. We apply the least square method for the four direction recognition and a support vector machine library for the handwritten digit recognition. Experimental results show that the proposed system has great potential on future human-machine development.
KW - handwritten digit
KW - Kinect
KW - pattern recongition
KW - support vector machine
UR - http://www.scopus.com/inward/record.url?scp=84875648416&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875648416&partnerID=8YFLogxK
U2 - 10.1109/ISPACS.2012.6473522
DO - 10.1109/ISPACS.2012.6473522
M3 - Conference contribution
AN - SCOPUS:84875648416
SN - 9781467350815
SP - 414
EP - 419
BT - ISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems
ER -