Random Forest with Adaptive Local Template for Pedestrian Detection
Joint Authors
Li, Tao
Xiang, Tao
Ye, Mao
Liu, Zijian
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Pedestrian detection with large intraclass variations is still a challenging task in computer vision.
In this paper, we propose a novel pedestrian detection method based on Random Forest.
Firstly, we generate a few local templates with different sizes and different locations in positive exemplars.
Then, the Random Forest is built whose splitting functions are optimized by maximizing class purity of matching the local templates to the training samples, respectively.
To improve the classification accuracy, we adopt a boosting-like algorithm to update the weights of the training samples in a layer-wise fashion.
During detection, the trained Random Forest will vote the category when a sliding window is input.
Our contributions are the splitting functions based on local template matching with adaptive size and location and iteratively weight updating method.
We evaluate the proposed method on 2 well-known challenging datasets: TUD pedestrians and INRIA pedestrians.
The experimental results demonstrate that our method achieves state-of-the-art or competitive performance.
American Psychological Association (APA)
Xiang, Tao& Li, Tao& Ye, Mao& Liu, Zijian. 2015. Random Forest with Adaptive Local Template for Pedestrian Detection. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074675
Modern Language Association (MLA)
Xiang, Tao…[et al.]. Random Forest with Adaptive Local Template for Pedestrian Detection. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1074675
American Medical Association (AMA)
Xiang, Tao& Li, Tao& Ye, Mao& Liu, Zijian. Random Forest with Adaptive Local Template for Pedestrian Detection. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074675
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074675