Research on Fast Pedestrian Detection Algorithm Based on Autoencoding Neural Network and AdaBoost
In order to solve the problem of low accuracy of pedestrian detection of real traffic cameras and high missed detection rate of small target pedestrians, this paper combines autoencoding neural network and AdaBoost to construct a fast pedestrian detection algorithm. Aiming at the problem that a sing...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5548476 |
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| _version_ | 1832550161009606656 |
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| author | Hongzhi Zhou Gan Yu |
| author_facet | Hongzhi Zhou Gan Yu |
| author_sort | Hongzhi Zhou |
| collection | DOAJ |
| description | In order to solve the problem of low accuracy of pedestrian detection of real traffic cameras and high missed detection rate of small target pedestrians, this paper combines autoencoding neural network and AdaBoost to construct a fast pedestrian detection algorithm. Aiming at the problem that a single high-level output feature map has insufficient ability to express pedestrian features and existing methods cannot effectively select appropriate multilevel features, this paper improves the traditional AdaBoost algorithm structure, that is, the sample weight update formula and the strong classifier output formula are reset, and the two-input AdaBoost-DBN classification algorithm is proposed. Moreover, in view of the problem that the fusion video is not smoothly played, this paper considers the motion information of the video object, performs pixel interpolation by motion compensation, and restores the frame rate of the original video by reconstructing the dropped interframe image. Through experimental research, we can see that the algorithm constructed in this paper has a certain effect. |
| format | Article |
| id | doaj-art-af8517697fe04cd4b41238f53706c5e3 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-af8517697fe04cd4b41238f53706c5e32025-02-03T06:07:37ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55484765548476Research on Fast Pedestrian Detection Algorithm Based on Autoencoding Neural Network and AdaBoostHongzhi Zhou0Gan Yu1College of Information Engineering, Fuyang Normal University, Fuyang, Anhui 236041, ChinaCollege of Information Engineering, Fuyang Normal University, Fuyang, Anhui 236041, ChinaIn order to solve the problem of low accuracy of pedestrian detection of real traffic cameras and high missed detection rate of small target pedestrians, this paper combines autoencoding neural network and AdaBoost to construct a fast pedestrian detection algorithm. Aiming at the problem that a single high-level output feature map has insufficient ability to express pedestrian features and existing methods cannot effectively select appropriate multilevel features, this paper improves the traditional AdaBoost algorithm structure, that is, the sample weight update formula and the strong classifier output formula are reset, and the two-input AdaBoost-DBN classification algorithm is proposed. Moreover, in view of the problem that the fusion video is not smoothly played, this paper considers the motion information of the video object, performs pixel interpolation by motion compensation, and restores the frame rate of the original video by reconstructing the dropped interframe image. Through experimental research, we can see that the algorithm constructed in this paper has a certain effect.http://dx.doi.org/10.1155/2021/5548476 |
| spellingShingle | Hongzhi Zhou Gan Yu Research on Fast Pedestrian Detection Algorithm Based on Autoencoding Neural Network and AdaBoost Complexity |
| title | Research on Fast Pedestrian Detection Algorithm Based on Autoencoding Neural Network and AdaBoost |
| title_full | Research on Fast Pedestrian Detection Algorithm Based on Autoencoding Neural Network and AdaBoost |
| title_fullStr | Research on Fast Pedestrian Detection Algorithm Based on Autoencoding Neural Network and AdaBoost |
| title_full_unstemmed | Research on Fast Pedestrian Detection Algorithm Based on Autoencoding Neural Network and AdaBoost |
| title_short | Research on Fast Pedestrian Detection Algorithm Based on Autoencoding Neural Network and AdaBoost |
| title_sort | research on fast pedestrian detection algorithm based on autoencoding neural network and adaboost |
| url | http://dx.doi.org/10.1155/2021/5548476 |
| work_keys_str_mv | AT hongzhizhou researchonfastpedestriandetectionalgorithmbasedonautoencodingneuralnetworkandadaboost AT ganyu researchonfastpedestriandetectionalgorithmbasedonautoencodingneuralnetworkandadaboost |