Abstract
Hand gesture interfaces are more intuitive and convenient than traditional interfaces. They are the most important parts in the relationship between users and devices. Hand tracking for hand gesture interfaces is an active area of research in image processing. However, previous works have limits such as requiring the use of multiple camera or sensor, working only with single color background, etc. This paper proposes a real-time both hands tracking algorithm based on "CAMshift (Continuous Adaptive Mean Shift Algorithm)" using only a single camera in multi-color backgrounds. In order to track hands robustly, the proposed algorithm uses "motion mask" to combine color and movement probability distributions and "probability reduction" for multi-hand tracking in non-limiting environments. Experimental results demonstrate that this algorithm can precisely track both hands of an operator in multi-color backgrounds and process the VGA size input sequences from a web camera in real time (about 25 fps).
| Original language | English |
|---|---|
| Title of host publication | 2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012 |
| Publication status | Published - 2012 |
| Event | 2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012 - Hollywood, CA Duration: 2012 Dec 3 → 2012 Dec 6 |
Other
| Other | 2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012 |
|---|---|
| City | Hollywood, CA |
| Period | 12/12/3 → 12/12/6 |
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ASJC Scopus subject areas
- Information Systems
Cite this
Real-time both hands tracking using CAMshift with motion mask and probability reduction by motion prediction. / Araki, Ryosuke; Gohshi, Seiichi; Ikenaga, Takeshi.
2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012. 2012. 6411770.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Real-time both hands tracking using CAMshift with motion mask and probability reduction by motion prediction
AU - Araki, Ryosuke
AU - Gohshi, Seiichi
AU - Ikenaga, Takeshi
PY - 2012
Y1 - 2012
N2 - Hand gesture interfaces are more intuitive and convenient than traditional interfaces. They are the most important parts in the relationship between users and devices. Hand tracking for hand gesture interfaces is an active area of research in image processing. However, previous works have limits such as requiring the use of multiple camera or sensor, working only with single color background, etc. This paper proposes a real-time both hands tracking algorithm based on "CAMshift (Continuous Adaptive Mean Shift Algorithm)" using only a single camera in multi-color backgrounds. In order to track hands robustly, the proposed algorithm uses "motion mask" to combine color and movement probability distributions and "probability reduction" for multi-hand tracking in non-limiting environments. Experimental results demonstrate that this algorithm can precisely track both hands of an operator in multi-color backgrounds and process the VGA size input sequences from a web camera in real time (about 25 fps).
AB - Hand gesture interfaces are more intuitive and convenient than traditional interfaces. They are the most important parts in the relationship between users and devices. Hand tracking for hand gesture interfaces is an active area of research in image processing. However, previous works have limits such as requiring the use of multiple camera or sensor, working only with single color background, etc. This paper proposes a real-time both hands tracking algorithm based on "CAMshift (Continuous Adaptive Mean Shift Algorithm)" using only a single camera in multi-color backgrounds. In order to track hands robustly, the proposed algorithm uses "motion mask" to combine color and movement probability distributions and "probability reduction" for multi-hand tracking in non-limiting environments. Experimental results demonstrate that this algorithm can precisely track both hands of an operator in multi-color backgrounds and process the VGA size input sequences from a web camera in real time (about 25 fps).
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UR - http://www.scopus.com/inward/citedby.url?scp=84874416114&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84874416114
SN - 9780615700502
BT - 2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012
ER -