Front-Vehicle Detection in Video Images Based on Temporal and Spatial Characteristics
Assisted driving and unmanned driving have been areas of focus for both industry and academia. Front-vehicle detection technology, a key component of both types of driving, has also attracted great interest from researchers. In this paper, to achieve front-vehicle detection in unmanned or assisted d...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/7/1728 |
| _version_ | 1811300331902992384 |
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| author | Bo Yang Sheng Zhang Yan Tian Bijun Li |
| author_facet | Bo Yang Sheng Zhang Yan Tian Bijun Li |
| author_sort | Bo Yang |
| collection | DOAJ |
| description | Assisted driving and unmanned driving have been areas of focus for both industry and academia. Front-vehicle detection technology, a key component of both types of driving, has also attracted great interest from researchers. In this paper, to achieve front-vehicle detection in unmanned or assisted driving, a vision-based, efficient, and fast front-vehicle detection method based on the spatial and temporal characteristics of the front vehicle is proposed. First, a method to extract the motion vector of the front vehicle is put forward based on Oriented FAST and Rotated BRIEF (ORB) and the spatial position constraint. Then, by analyzing the differences between the motion vectors of the vehicle and those of the background, feature points of the vehicle are extracted. Finally, a feature-point clustering method based on a combination of temporal and spatial characteristics are applied to realize front-vehicle detection. The effectiveness of the proposed algorithm is verified using a large number of videos. |
| first_indexed | 2024-04-13T06:50:34Z |
| format | Article |
| id | doaj.art-871e621e4a854f71ae901d2a8f8b9153 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:50:34Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-871e621e4a854f71ae901d2a8f8b91532022-12-22T02:57:26ZengMDPI AGSensors1424-82202019-04-01197172810.3390/s19071728s19071728Front-Vehicle Detection in Video Images Based on Temporal and Spatial CharacteristicsBo Yang0Sheng Zhang1Yan Tian2Bijun Li3State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, ChinaSchool of Electronic Information and Communication, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Electronic Information and Communication, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, ChinaAssisted driving and unmanned driving have been areas of focus for both industry and academia. Front-vehicle detection technology, a key component of both types of driving, has also attracted great interest from researchers. In this paper, to achieve front-vehicle detection in unmanned or assisted driving, a vision-based, efficient, and fast front-vehicle detection method based on the spatial and temporal characteristics of the front vehicle is proposed. First, a method to extract the motion vector of the front vehicle is put forward based on Oriented FAST and Rotated BRIEF (ORB) and the spatial position constraint. Then, by analyzing the differences between the motion vectors of the vehicle and those of the background, feature points of the vehicle are extracted. Finally, a feature-point clustering method based on a combination of temporal and spatial characteristics are applied to realize front-vehicle detection. The effectiveness of the proposed algorithm is verified using a large number of videos.https://www.mdpi.com/1424-8220/19/7/1728motion vectorvanishing pointclusteringfront-vehicle detection |
| spellingShingle | Bo Yang Sheng Zhang Yan Tian Bijun Li Front-Vehicle Detection in Video Images Based on Temporal and Spatial Characteristics Sensors motion vector vanishing point clustering front-vehicle detection |
| title | Front-Vehicle Detection in Video Images Based on Temporal and Spatial Characteristics |
| title_full | Front-Vehicle Detection in Video Images Based on Temporal and Spatial Characteristics |
| title_fullStr | Front-Vehicle Detection in Video Images Based on Temporal and Spatial Characteristics |
| title_full_unstemmed | Front-Vehicle Detection in Video Images Based on Temporal and Spatial Characteristics |
| title_short | Front-Vehicle Detection in Video Images Based on Temporal and Spatial Characteristics |
| title_sort | front vehicle detection in video images based on temporal and spatial characteristics |
| topic | motion vector vanishing point clustering front-vehicle detection |
| url | https://www.mdpi.com/1424-8220/19/7/1728 |
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