Abstract
An in-air hand gesture signature verification system that doesn't require a handheld device is proposed. depth image sensor captures signature gestures and records each signature as a 3D volume. A structured projection is then applied to the directionally accumulated images for feature extraction. For trajectory features, the fingertip and palm-mass trajectories are extracted from a signature data sample. Subsequently, these features are fused for possible performance enhancement. The signature data acquired using the prototype system contains not only the region of the body but also noise such as imaging distortion and background clutter. The usage of palm-mass center features for identity verification yields better accuracies than that of using the fingertip features. This could be due to stability of the extracted features.
| Original language | English |
|---|---|
| Pages (from-to) | 52-55 |
| Number of pages | 4 |
| Journal | IEEE Intelligent Systems |
| Volume | 28 |
| Issue number | 6 |
| Publication status | Published - 2013 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Artificial Intelligence
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A system for signature verification based on horizontal and vertical components in hand gestures. / Oh, Beom Seok; Jeon, Jehyoung; Toh, Kar Ann; Teoh, Andrew Beng Jin; Kim, Jaihie.
In: IEEE Intelligent Systems, Vol. 28, No. 6, 01.01.2013, p. 52-55.Research output: Contribution to journal › Article
TY - JOUR
T1 - A system for signature verification based on horizontal and vertical components in hand gestures
AU - Oh, Beom Seok
AU - Jeon, Jehyoung
AU - Toh, Kar Ann
AU - Teoh, Andrew Beng Jin
AU - Kim, Jaihie
PY - 2013/1/1
Y1 - 2013/1/1
N2 - An in-air hand gesture signature verification system that doesn't require a handheld device is proposed. depth image sensor captures signature gestures and records each signature as a 3D volume. A structured projection is then applied to the directionally accumulated images for feature extraction. For trajectory features, the fingertip and palm-mass trajectories are extracted from a signature data sample. Subsequently, these features are fused for possible performance enhancement. The signature data acquired using the prototype system contains not only the region of the body but also noise such as imaging distortion and background clutter. The usage of palm-mass center features for identity verification yields better accuracies than that of using the fingertip features. This could be due to stability of the extracted features.
AB - An in-air hand gesture signature verification system that doesn't require a handheld device is proposed. depth image sensor captures signature gestures and records each signature as a 3D volume. A structured projection is then applied to the directionally accumulated images for feature extraction. For trajectory features, the fingertip and palm-mass trajectories are extracted from a signature data sample. Subsequently, these features are fused for possible performance enhancement. The signature data acquired using the prototype system contains not only the region of the body but also noise such as imaging distortion and background clutter. The usage of palm-mass center features for identity verification yields better accuracies than that of using the fingertip features. This could be due to stability of the extracted features.
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UR - http://www.scopus.com/inward/citedby.url?scp=84928950043&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84928950043
VL - 28
SP - 52
EP - 55
JO - IEEE Intelligent Systems
JF - IEEE Intelligent Systems
SN - 1541-1672
IS - 6
ER -