A Calculation Method for Vehicle Movement Reconstruction from Videos
This paper proposes a new enhanced method based on one-dimensional direct linear transformation for estimating vehicle movement states in video sequences. The proposed method utilizes a contoured structure of target vehicles, and the data collection procedure is found to be relatively stable and eff...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/8896826 |
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| _version_ | 1832547362185150464 |
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| author | Hao Feng Weiguo Shi Feng Chen Young-Ji Byon Weiwei Heng Shaoyou Pan |
| author_facet | Hao Feng Weiguo Shi Feng Chen Young-Ji Byon Weiwei Heng Shaoyou Pan |
| author_sort | Hao Feng |
| collection | DOAJ |
| description | This paper proposes a new enhanced method based on one-dimensional direct linear transformation for estimating vehicle movement states in video sequences. The proposed method utilizes a contoured structure of target vehicles, and the data collection procedure is found to be relatively stable and effective, providing a better applicability. The movements of vehicles in the video are captured by active calibration regions while the spatial consistency between the vehicle’s driving track and the calibration information are in sync. The vehicle movement states in the verification phase are estimated using the proposed method first, and then the estimated states are compared with the actual movement states recorded in the experimental test. The results show that, in the case of camera perspective of 90 degrees, in all driving states of low speed, high speed, or deceleration, the error between estimated speed and recorded speed is less than 1.5%, the error of accelerations is less than 7%, and the error of distances is less than 2%; similarly, in the case of camera perspective of 30 degrees, the errors of speeds, distances, and accelerations are less than 4%, 5%, and 10%, respectively. It is found that the proposed method is superior to other existing methods. |
| format | Article |
| id | doaj-art-693c93e71e234d71a40fe37295f64cc0 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-693c93e71e234d71a40fe37295f64cc02025-02-03T06:44:56ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/88968268896826A Calculation Method for Vehicle Movement Reconstruction from VideosHao Feng0Weiguo Shi1Feng Chen2Young-Ji Byon3Weiwei Heng4Shaoyou Pan5Academy of Forensic Science, Shanghai 200063, ChinaKey Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, ChinaKey Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, ChinaDepartment of Civil Infrastructure and Environmental Engineering, Khalifa University of Science and Technology, P.O. Box 127788, Abu Dhabi, UAEAcademy of Forensic Science, Shanghai 200063, ChinaAcademy of Forensic Science, Shanghai 200063, ChinaThis paper proposes a new enhanced method based on one-dimensional direct linear transformation for estimating vehicle movement states in video sequences. The proposed method utilizes a contoured structure of target vehicles, and the data collection procedure is found to be relatively stable and effective, providing a better applicability. The movements of vehicles in the video are captured by active calibration regions while the spatial consistency between the vehicle’s driving track and the calibration information are in sync. The vehicle movement states in the verification phase are estimated using the proposed method first, and then the estimated states are compared with the actual movement states recorded in the experimental test. The results show that, in the case of camera perspective of 90 degrees, in all driving states of low speed, high speed, or deceleration, the error between estimated speed and recorded speed is less than 1.5%, the error of accelerations is less than 7%, and the error of distances is less than 2%; similarly, in the case of camera perspective of 30 degrees, the errors of speeds, distances, and accelerations are less than 4%, 5%, and 10%, respectively. It is found that the proposed method is superior to other existing methods.http://dx.doi.org/10.1155/2020/8896826 |
| spellingShingle | Hao Feng Weiguo Shi Feng Chen Young-Ji Byon Weiwei Heng Shaoyou Pan A Calculation Method for Vehicle Movement Reconstruction from Videos Journal of Advanced Transportation |
| title | A Calculation Method for Vehicle Movement Reconstruction from Videos |
| title_full | A Calculation Method for Vehicle Movement Reconstruction from Videos |
| title_fullStr | A Calculation Method for Vehicle Movement Reconstruction from Videos |
| title_full_unstemmed | A Calculation Method for Vehicle Movement Reconstruction from Videos |
| title_short | A Calculation Method for Vehicle Movement Reconstruction from Videos |
| title_sort | calculation method for vehicle movement reconstruction from videos |
| url | http://dx.doi.org/10.1155/2020/8896826 |
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