Hand Detection Using Cascade of Softmax Classifiers
Joint Authors
Zhao, Yan-Guo
Zheng, Feng
Song, Zhan
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-10
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
Sliding-window based multiclass hand posture detections are often performed by detecting postures of each predefined category using an independent detector, which makes it lack efficiency and results in high postures confusion rates in real-time applications.
To tackle such problems, in this work, an efficient cascade detector that integrates multiple softmax-based binary (SftB) models and a softmax-based multiclass (SftM) model is investigated to perform multiclass posture detection in parallel.
The SftB models are used to distinguish the predefined postures from the background regions, and the SftM model is applied to discriminate among all the predefined hand posture categories.
Another usage of the cascade structure is that it could effectively decompose the complexity of background pattern space and therefore improve the detection accuracy.
In addition, to balance the detection accuracy and efficiency, the HOG features of increasing resolutions will be adopted by classifiers of increasing stage-levels in the cascade structure.
The experiments are implemented under various scenarios with complicated background and challenging lightings.
Results show the superiority of the proposed SftB classifiers over the traditional binary classifiers such as logistic regression, as well as the accuracy and efficiency improvements brought by the softmax-based cascade architecture compared with the noncascade multiclass softmax detectors.
American Psychological Association (APA)
Zhao, Yan-Guo& Zheng, Feng& Song, Zhan. 2018. Hand Detection Using Cascade of Softmax Classifiers. Advances in Multimedia،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1118492
Modern Language Association (MLA)
Zhao, Yan-Guo…[et al.]. Hand Detection Using Cascade of Softmax Classifiers. Advances in Multimedia No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1118492
American Medical Association (AMA)
Zhao, Yan-Guo& Zheng, Feng& Song, Zhan. Hand Detection Using Cascade of Softmax Classifiers. Advances in Multimedia. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1118492
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118492