Integrated Velocity Measurement Algorithm Based on Optical Flow and Scale-Invariant Feature Transform
The pyramid Lucas-Kanade (LK) optical flow algorithm has been widely used in velocity measurement applications. However, these applications are limited by some shortcomings of the algorithm, such as its slow calculation speed and susceptibility to illumination changes. To solve these problems, a dat...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8879496/ |
| _version_ | 1818855252436189184 |
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| author | Xiaochen Liu Xiaoting Guo Donghua Zhao Huiliang Cao Jun Tang Chenguang Wang Chong Shen Jun Liu |
| author_facet | Xiaochen Liu Xiaoting Guo Donghua Zhao Huiliang Cao Jun Tang Chenguang Wang Chong Shen Jun Liu |
| author_sort | Xiaochen Liu |
| collection | DOAJ |
| description | The pyramid Lucas-Kanade (LK) optical flow algorithm has been widely used in velocity measurement applications. However, these applications are limited by some shortcomings of the algorithm, such as its slow calculation speed and susceptibility to illumination changes. To solve these problems, a data fusion scheme based on the scale-invariant feature transform (SIFT) and optical flow is proposed to alleviate the dependence of the optical flow on the illumination conditions. In addition, an improved cubature Kalman filter (CKF) based on multi-rate residual correction (CKF-MRC) is proposed to solve the problem of inconsistency between the sampling frequencies of the SIFT and the optical flow, and takes full advantage of the high sampling frequency of SIFT. The experimental results demonstrate that the proposed CKF-MRC method can effectively improve the accuracy of velocity measurement under variable illumination conditions with a high sampling frequency. |
| first_indexed | 2024-12-19T08:05:39Z |
| format | Article |
| id | doaj.art-a73fae69bf09475fab7fce9803c744c7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T08:05:39Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-a73fae69bf09475fab7fce9803c744c72022-12-21T20:29:45ZengIEEEIEEE Access2169-35362019-01-01715333815334810.1109/ACCESS.2019.29488378879496Integrated Velocity Measurement Algorithm Based on Optical Flow and Scale-Invariant Feature TransformXiaochen Liu0Xiaoting Guo1https://orcid.org/0000-0002-4892-1058Donghua Zhao2Huiliang Cao3Jun Tang4Chenguang Wang5Chong Shen6https://orcid.org/0000-0002-6046-6051Jun Liu7Key Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, School of Instrument and Electronics, North University of China, Taiyuan, ChinaKey Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, School of Instrument and Electronics, North University of China, Taiyuan, ChinaKey Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, School of Instrument and Electronics, North University of China, Taiyuan, ChinaKey Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, School of Instrument and Electronics, North University of China, Taiyuan, ChinaKey Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, School of Instrument and Electronics, North University of China, Taiyuan, ChinaSchool of Information and Communication Engineering, North University of China, Taiyuan, ChinaKey Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, School of Instrument and Electronics, North University of China, Taiyuan, ChinaKey Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, School of Instrument and Electronics, North University of China, Taiyuan, ChinaThe pyramid Lucas-Kanade (LK) optical flow algorithm has been widely used in velocity measurement applications. However, these applications are limited by some shortcomings of the algorithm, such as its slow calculation speed and susceptibility to illumination changes. To solve these problems, a data fusion scheme based on the scale-invariant feature transform (SIFT) and optical flow is proposed to alleviate the dependence of the optical flow on the illumination conditions. In addition, an improved cubature Kalman filter (CKF) based on multi-rate residual correction (CKF-MRC) is proposed to solve the problem of inconsistency between the sampling frequencies of the SIFT and the optical flow, and takes full advantage of the high sampling frequency of SIFT. The experimental results demonstrate that the proposed CKF-MRC method can effectively improve the accuracy of velocity measurement under variable illumination conditions with a high sampling frequency.https://ieeexplore.ieee.org/document/8879496/Cubature Kalman filteroptical flowresidual error correctionscale-invariant feature transform |
| spellingShingle | Xiaochen Liu Xiaoting Guo Donghua Zhao Huiliang Cao Jun Tang Chenguang Wang Chong Shen Jun Liu Integrated Velocity Measurement Algorithm Based on Optical Flow and Scale-Invariant Feature Transform IEEE Access Cubature Kalman filter optical flow residual error correction scale-invariant feature transform |
| title | Integrated Velocity Measurement Algorithm Based on Optical Flow and Scale-Invariant Feature Transform |
| title_full | Integrated Velocity Measurement Algorithm Based on Optical Flow and Scale-Invariant Feature Transform |
| title_fullStr | Integrated Velocity Measurement Algorithm Based on Optical Flow and Scale-Invariant Feature Transform |
| title_full_unstemmed | Integrated Velocity Measurement Algorithm Based on Optical Flow and Scale-Invariant Feature Transform |
| title_short | Integrated Velocity Measurement Algorithm Based on Optical Flow and Scale-Invariant Feature Transform |
| title_sort | integrated velocity measurement algorithm based on optical flow and scale invariant feature transform |
| topic | Cubature Kalman filter optical flow residual error correction scale-invariant feature transform |
| url | https://ieeexplore.ieee.org/document/8879496/ |
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