Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian Detection
This work presents the fusion of integral channel features to improve the effectiveness and efficiency of pedestrian detection. The proposed method combines the histogram of oriented gradient (HOG) and local binary pattern (LBP) features by a concatenated fusion method. Although neural network (NN)...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2013/436062 |
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| author | Song-Zhi Su Shu-Yuan Chen |
| author_facet | Song-Zhi Su Shu-Yuan Chen |
| author_sort | Song-Zhi Su |
| collection | DOAJ |
| description | This work presents the fusion of integral channel features to improve the effectiveness and efficiency of pedestrian detection. The proposed method combines the histogram of oriented gradient (HOG) and local binary pattern (LBP) features by a concatenated fusion method. Although neural network (NN) is an efficient tool for classification, the time complexity is heavy. Hence, we choose support vector machine (SVM) with the histogram intersection kernel (HIK) as a classifier. On the other hand, although many datasets have been collected for pedestrian detection, few are designed to detect pedestrians in low-resolution visual images and at night time. This work collects two new pedestrian datasets—one for low-resolution visual images and one for near-infrared images—to evaluate detection performance on various image types and at different times. The proposed fusion method uses only images from the INRIA dataset for training but works on the two newly collected datasets, thereby avoiding the training overhead for cross-datasets. The experimental results verify that the proposed method has high detection accuracies even in the variations of image types and time slots. |
| format | Article |
| id | doaj-art-d27a90bc06b0419aaae73bc3d1a6b49d |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-d27a90bc06b0419aaae73bc3d1a6b49d2025-02-03T05:53:37ZengWileyAbstract and Applied Analysis1085-33751687-04092013-01-01201310.1155/2013/436062436062Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian DetectionSong-Zhi Su0Shu-Yuan Chen1School of Information Science and Technology, Xiamen University, Xiamen, Fujian Province 361005, ChinaDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, TaiwanThis work presents the fusion of integral channel features to improve the effectiveness and efficiency of pedestrian detection. The proposed method combines the histogram of oriented gradient (HOG) and local binary pattern (LBP) features by a concatenated fusion method. Although neural network (NN) is an efficient tool for classification, the time complexity is heavy. Hence, we choose support vector machine (SVM) with the histogram intersection kernel (HIK) as a classifier. On the other hand, although many datasets have been collected for pedestrian detection, few are designed to detect pedestrians in low-resolution visual images and at night time. This work collects two new pedestrian datasets—one for low-resolution visual images and one for near-infrared images—to evaluate detection performance on various image types and at different times. The proposed fusion method uses only images from the INRIA dataset for training but works on the two newly collected datasets, thereby avoiding the training overhead for cross-datasets. The experimental results verify that the proposed method has high detection accuracies even in the variations of image types and time slots.http://dx.doi.org/10.1155/2013/436062 |
| spellingShingle | Song-Zhi Su Shu-Yuan Chen Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian Detection Abstract and Applied Analysis |
| title | Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian Detection |
| title_full | Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian Detection |
| title_fullStr | Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian Detection |
| title_full_unstemmed | Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian Detection |
| title_short | Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian Detection |
| title_sort | analysis of feature fusion based on hik svm and its application for pedestrian detection |
| url | http://dx.doi.org/10.1155/2013/436062 |
| work_keys_str_mv | AT songzhisu analysisoffeaturefusionbasedonhiksvmanditsapplicationforpedestriandetection AT shuyuanchen analysisoffeaturefusionbasedonhiksvmanditsapplicationforpedestriandetection |