Human Action Recognition Based on Fusion Features Extraction of Adaptive Background Subtraction and Optical Flow Model
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-16
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
A novel method based on hybrid feature is proposed for human action recognition in video image sequences, which includes two stages of feature extraction and action recognition.
Firstly, we use adaptive background subtraction algorithm to extract global silhouette feature and optical flow model to extract local optical flow feature.
Then we combine global silhouette feature vector and local optical flow feature vector to form a hybrid feature vector.
Secondly, in order to improve the recognition accuracy, we use an optimized Multiple Instance Learning algorithm to recognize human actions, in which an Iterative Querying Heuristic (IQH) optimization algorithm is used to train the Multiple Instance Learning model.
We demonstrate that our hybrid feature-based action representation can effectively classify novel actions on two different data sets.
Experiments show that our results are comparable to, and significantly better than, the results of two state-of-the-art approaches on these data sets, which meets the requirements of stable, reliable, high precision, and anti-interference ability and so forth.
American Psychological Association (APA)
Zhu, Shaoping& Xia, Limin. 2015. Human Action Recognition Based on Fusion Features Extraction of Adaptive Background Subtraction and Optical Flow Model. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073705
Modern Language Association (MLA)
Zhu, Shaoping& Xia, Limin. Human Action Recognition Based on Fusion Features Extraction of Adaptive Background Subtraction and Optical Flow Model. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1073705
American Medical Association (AMA)
Zhu, Shaoping& Xia, Limin. Human Action Recognition Based on Fusion Features Extraction of Adaptive Background Subtraction and Optical Flow Model. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073705
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073705