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Real-Time Depth-Based Hand Detection and Tracking
Joint Authors
Joo, Sung-Il
Weon, Sun-Hee
Choi, Hyung-Il
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-09
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
This paper illustrates the hand detection and tracking method that operates in real time on depth data.
To detect a hand region, we propose the classifier that combines a boosting and a cascade structure.
The classifier uses the features of depth-difference at the stage of detection as well as learning.
The features of each candidate segment are to be computed by subtracting the averages of depth values of subblocks from the central depth value of the segment.
The features are selectively employed according to their discriminating power when constructing the classifier.
To predict a hand region in a successive frame, a seed point in the next frame is to be determined.
Starting from the seed point, a region growing scheme is applied to obtain a hand region.
To determine the central point of a hand, we propose the so-called Depth Adaptive Mean Shift algorithm.
DAM-Shift is a variant of CAM-Shift (Bradski, 1998), where the size of the search disk varies according to the depth of a hand.
We have evaluated the proposed hand detection and tracking algorithm by comparing it against the existing AdaBoost (Friedman et al., 2000) qualitatively and quantitatively.
We have analyzed the tracking accuracy through performance tests in various situations.
American Psychological Association (APA)
Joo, Sung-Il& Weon, Sun-Hee& Choi, Hyung-Il. 2014. Real-Time Depth-Based Hand Detection and Tracking. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1049072
Modern Language Association (MLA)
Joo, Sung-Il…[et al.]. Real-Time Depth-Based Hand Detection and Tracking. The Scientific World Journal No. 2014 (2014), pp.1-17.
https://search.emarefa.net/detail/BIM-1049072
American Medical Association (AMA)
Joo, Sung-Il& Weon, Sun-Hee& Choi, Hyung-Il. Real-Time Depth-Based Hand Detection and Tracking. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1049072
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049072