Thermal Sensor-Based Multiple Object Tracking for Intelligent Livestock Breeding
Visual object tracking is an essential technique for constructing intelligent livestock management systems. Behavior patterns estimated from the trajectories of animals provide substantial useful information related to estrus cycle, disease prognosis and so on. However, similar colors and shapes bet...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8114167/ |
| _version_ | 1818415333541675008 |
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| author | Wonjun Kim Yong Beom Cho Sangrak Lee |
| author_facet | Wonjun Kim Yong Beom Cho Sangrak Lee |
| author_sort | Wonjun Kim |
| collection | DOAJ |
| description | Visual object tracking is an essential technique for constructing intelligent livestock management systems. Behavior patterns estimated from the trajectories of animals provide substantial useful information related to estrus cycle, disease prognosis and so on. However, similar colors and shapes between animals often lead to the failure of tracking multiple objects, and the background clutter of the breeding space further makes the problem intractable. In this paper, we propose a novel method for tracking animals using a single thermal sensor. The key idea of the proposed method is to represent the foreground (i.e., animals) easily obtained by a simple thresholding in a thermal frame as a topographic surface, which is very helpful for finding the boundary of each object even in cases with overlapping. Based on the segmentation results derived from morphological operations on the topographic surface, the center positions of all the animals are consistently updated with an efficient refinement scheme that is robust to the abrupt motions of animals. Experimental results using various thermal video sequences demonstrate the efficiency and robustness of our method for tracking animals in a breeding space compared to previous approaches proposed in the literature. |
| first_indexed | 2024-12-14T11:33:20Z |
| format | Article |
| id | doaj.art-bc6b066ffd6344df854597483a8da70e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T11:33:20Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-bc6b066ffd6344df854597483a8da70e2022-12-21T23:03:10ZengIEEEIEEE Access2169-35362017-01-015274532746310.1109/ACCESS.2017.27750408114167Thermal Sensor-Based Multiple Object Tracking for Intelligent Livestock BreedingWonjun Kim0https://orcid.org/0000-0001-5121-5931Yong Beom Cho1Sangrak Lee2Department of Electronics Engineering, Konkuk University, Seoul, South KoreaDepartment of Electronics Engineering, Konkuk University, Seoul, South KoreaDepartment of Animal Science and Technology, Konkuk University, Seoul, South KoreaVisual object tracking is an essential technique for constructing intelligent livestock management systems. Behavior patterns estimated from the trajectories of animals provide substantial useful information related to estrus cycle, disease prognosis and so on. However, similar colors and shapes between animals often lead to the failure of tracking multiple objects, and the background clutter of the breeding space further makes the problem intractable. In this paper, we propose a novel method for tracking animals using a single thermal sensor. The key idea of the proposed method is to represent the foreground (i.e., animals) easily obtained by a simple thresholding in a thermal frame as a topographic surface, which is very helpful for finding the boundary of each object even in cases with overlapping. Based on the segmentation results derived from morphological operations on the topographic surface, the center positions of all the animals are consistently updated with an efficient refinement scheme that is robust to the abrupt motions of animals. Experimental results using various thermal video sequences demonstrate the efficiency and robustness of our method for tracking animals in a breeding space compared to previous approaches proposed in the literature.https://ieeexplore.ieee.org/document/8114167/Visual object trackingintelligent livestock managementthermal sensortopographic surface-based segmentationoverlapped cases |
| spellingShingle | Wonjun Kim Yong Beom Cho Sangrak Lee Thermal Sensor-Based Multiple Object Tracking for Intelligent Livestock Breeding IEEE Access Visual object tracking intelligent livestock management thermal sensor topographic surface-based segmentation overlapped cases |
| title | Thermal Sensor-Based Multiple Object Tracking for Intelligent Livestock Breeding |
| title_full | Thermal Sensor-Based Multiple Object Tracking for Intelligent Livestock Breeding |
| title_fullStr | Thermal Sensor-Based Multiple Object Tracking for Intelligent Livestock Breeding |
| title_full_unstemmed | Thermal Sensor-Based Multiple Object Tracking for Intelligent Livestock Breeding |
| title_short | Thermal Sensor-Based Multiple Object Tracking for Intelligent Livestock Breeding |
| title_sort | thermal sensor based multiple object tracking for intelligent livestock breeding |
| topic | Visual object tracking intelligent livestock management thermal sensor topographic surface-based segmentation overlapped cases |
| url | https://ieeexplore.ieee.org/document/8114167/ |
| work_keys_str_mv | AT wonjunkim thermalsensorbasedmultipleobjecttrackingforintelligentlivestockbreeding AT yongbeomcho thermalsensorbasedmultipleobjecttrackingforintelligentlivestockbreeding AT sangraklee thermalsensorbasedmultipleobjecttrackingforintelligentlivestockbreeding |