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Improved Collaborative Representation Classifier Based on l2-Regularized for Human Action Recognition
Joint Authors
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-20
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Abstract EN
Human action recognition is an important recent challenging task.
Projecting depth images onto three depth motion maps (DMMs) and extracting deep convolutional neural network (DCNN) features are discriminant descriptor features to characterize the spatiotemporal information of a specific action from a sequence of depth images.
In this paper, a unified improved collaborative representation framework is proposed in which the probability that a test sample belongs to the collaborative subspace of all classes can be well defined and calculated.
The improved collaborative representation classifier (ICRC) based on l2-regularized for human action recognition is presented to maximize the likelihood that a test sample belongs to each class, then theoretical investigation into ICRC shows that it obtains a final classification by computing the likelihood for each class.
Coupled with the DMMs and DCNN features, experiments on depth image-based action recognition, including MSRAction3D and MSRGesture3D datasets, demonstrate that the proposed approach successfully using a distance-based representation classifier achieves superior performance over the state-of-the-art methods, including SRC, CRC, and SVM.
American Psychological Association (APA)
Huo, Shirui& Hu, Tianrui& Li, Ce. 2017. Improved Collaborative Representation Classifier Based on l2-Regularized for Human Action Recognition. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1175390
Modern Language Association (MLA)
Huo, Shirui…[et al.]. Improved Collaborative Representation Classifier Based on l2-Regularized for Human Action Recognition. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-6.
https://search.emarefa.net/detail/BIM-1175390
American Medical Association (AMA)
Huo, Shirui& Hu, Tianrui& Li, Ce. Improved Collaborative Representation Classifier Based on l2-Regularized for Human Action Recognition. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1175390
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175390