Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track Association
The multirotor has the capability to capture distant objects. Because the computing resources of the multirotor are limited, efficiency is an important factor to consider. In this paper, multiple target tracking with a multirotor at a long distance (~400 m) is addressed; the interacting multiple mod...
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| Format: | Article |
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MDPI AG
2021-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/23/11234 |
| _version_ | 1797508031159730176 |
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| author | Seokwon Yeom |
| author_facet | Seokwon Yeom |
| author_sort | Seokwon Yeom |
| collection | DOAJ |
| description | The multirotor has the capability to capture distant objects. Because the computing resources of the multirotor are limited, efficiency is an important factor to consider. In this paper, multiple target tracking with a multirotor at a long distance (~400 m) is addressed; the interacting multiple model (IMM) estimator combined with the directional track-to-track association (abbreviated as track association) is proposed. The previous work of the Kalman estimator with the track association approach is extended to the IMM estimator with the directional track association. The IMM estimator can handle multiple targets with various maneuvers. The track association scheme is modified in consideration of the direction of the target movement. The overall system is composed of moving object detection for measurement generation and multiple target tracking for state estimation. The moving object detection consists of frame-to-frame subtraction of three-color layers and thresholding, morphological operation, and false alarm removing based on the object size and shape properties. The centroid of the detected object is input into the next tracking stage. The track is initialized using the difference between two nearest points measured in consecutive frames. The measurement nearest to the state prediction is used to update the state of the target for measurement-to-track association. The directional track association tests both the hypothesis and the maximum deviation between the displacement and directions of two tracks followed by track selection, fusion, and termination. In the experiment, a multirotor flying at an altitude of 400 m captured 55 moving vehicles around a highway interchange for about 20 s. The tracking performance is evaluated for the IMMs using constant velocity (CV) and constant acceleration (CA) motion models. The IMM-CA with the directional track association scheme outperforms other methods with an average total track life of 91.7% and an average mean track life of 84.2%. |
| first_indexed | 2024-03-10T04:56:50Z |
| format | Article |
| id | doaj.art-071311983c584d36ba3569a38bb72479 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T04:56:50Z |
| publishDate | 2021-11-01 |
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| series | Applied Sciences |
| spelling | doaj.art-071311983c584d36ba3569a38bb724792023-11-23T02:04:44ZengMDPI AGApplied Sciences2076-34172021-11-0111231123410.3390/app112311234Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track AssociationSeokwon Yeom0School of ICT Eng., Daegu University, Gyeongsan 38453, KoreaThe multirotor has the capability to capture distant objects. Because the computing resources of the multirotor are limited, efficiency is an important factor to consider. In this paper, multiple target tracking with a multirotor at a long distance (~400 m) is addressed; the interacting multiple model (IMM) estimator combined with the directional track-to-track association (abbreviated as track association) is proposed. The previous work of the Kalman estimator with the track association approach is extended to the IMM estimator with the directional track association. The IMM estimator can handle multiple targets with various maneuvers. The track association scheme is modified in consideration of the direction of the target movement. The overall system is composed of moving object detection for measurement generation and multiple target tracking for state estimation. The moving object detection consists of frame-to-frame subtraction of three-color layers and thresholding, morphological operation, and false alarm removing based on the object size and shape properties. The centroid of the detected object is input into the next tracking stage. The track is initialized using the difference between two nearest points measured in consecutive frames. The measurement nearest to the state prediction is used to update the state of the target for measurement-to-track association. The directional track association tests both the hypothesis and the maximum deviation between the displacement and directions of two tracks followed by track selection, fusion, and termination. In the experiment, a multirotor flying at an altitude of 400 m captured 55 moving vehicles around a highway interchange for about 20 s. The tracking performance is evaluated for the IMMs using constant velocity (CV) and constant acceleration (CA) motion models. The IMM-CA with the directional track association scheme outperforms other methods with an average total track life of 91.7% and an average mean track life of 84.2%.https://www.mdpi.com/2076-3417/11/23/11234drone surveillancemoving object detectionmultiple target trackingdirectional track associationstate estimation |
| spellingShingle | Seokwon Yeom Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track Association Applied Sciences drone surveillance moving object detection multiple target tracking directional track association state estimation |
| title | Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track Association |
| title_full | Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track Association |
| title_fullStr | Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track Association |
| title_full_unstemmed | Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track Association |
| title_short | Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track Association |
| title_sort | long distance moving vehicle tracking with a multirotor based on imm directional track association |
| topic | drone surveillance moving object detection multiple target tracking directional track association state estimation |
| url | https://www.mdpi.com/2076-3417/11/23/11234 |
| work_keys_str_mv | AT seokwonyeom longdistancemovingvehicletrackingwithamultirotorbasedonimmdirectionaltrackassociation |