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A Pedestrian Detection Method Based on Genetic Algorithm for Optimize XGBoost Training Parameters

IEEE access, 2019, Vol.7, p.118310-118321 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2019.2936454 ;CODEN: IAECCG

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Title:
A Pedestrian Detection Method Based on Genetic Algorithm for Optimize XGBoost Training Parameters
Author: Jiang, Yu ; Tong, Guoxiang ; Yin, Henan ; Xiong, Naixue
Subjects: Boosting ; Classification algorithms ; Classifiers ; Feature extraction ; genetic algorithm ; Genetic algorithms ; histogram of oriented gradient features (HOG) ; Histograms ; Image color analysis ; local binary patterns (LBP) XGBoost classifier ; Machine learning ; Machine learning algorithms ; Pedestrain detection ; Pedestrians ; Process parameters ; Training
Is Part Of: IEEE access, 2019, Vol.7, p.118310-118321
Description: In this paper, we present a machine learning classifier which is used for pedestrian detection based on XGBoost. Our approach, the Genetic Algorithm is introduced to optimize the parameter tuning process during training an XGBoost model. In order to improve the classification accuracy, HOG and LBP features are used to describe pedestrians in a way of tandem fusion, then input into GA-XGBoost classifier proposed in this paper to form a new static image pedestrian detection algorithm. The pedestrian feature extraction and machine learning are decoupled by storing the extracted pedestrian feature as feature files in the experiment, so that training can be exacuted many times and algorithms can be camparied conveniently. Experimental show that our pedestrian detection algorithm has improved the accuracy of pedestrian detection in the static image. The Area Under the ROC Curve (AUC) value reaches 0.9913.
Publisher: Piscataway: IEEE
Language: English
Identifier: ISSN: 2169-3536
EISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2936454
CODEN: IAECCG
Source: IEEE Open Access Journals
DOAJ Directory of Open Access Journals

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A Pedestrian Detection Method Based on Genetic Algorithm for Optimize XGBoost Training Parameters

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2019.2936454 ;CODEN: IAECCG

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