{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T18:18:41Z","timestamp":1770142721974,"version":"3.49.0"},"reference-count":39,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Agriculture, Food and Rural Affairs","award":["421018-03"],"award-info":[{"award-number":["421018-03"]}]},{"name":"Ministry of Agriculture, Food and Rural Affairs","award":["421023-04"],"award-info":[{"award-number":["421023-04"]}]},{"name":"Ministry of Agriculture, Food and Rural Affairs","award":["NRF-2019R1A6A1A09031717"],"award-info":[{"award-number":["NRF-2019R1A6A1A09031717"]}]},{"name":"National Research Foundation of Korea (NRF)","award":["421018-03"],"award-info":[{"award-number":["421018-03"]}]},{"name":"National Research Foundation of Korea (NRF)","award":["421023-04"],"award-info":[{"award-number":["421023-04"]}]},{"name":"National Research Foundation of Korea (NRF)","award":["NRF-2019R1A6A1A09031717"],"award-info":[{"award-number":["NRF-2019R1A6A1A09031717"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Pig husbandry constitutes a significant segment within the broader framework of livestock farming, with porcine well-being emerging as a paramount concern due to its direct implications on pig breeding and production. An easily observable proxy for assessing the health of pigs lies in their daily patterns of movement. The daily movement patterns of pigs can be used as an indicator of their health, in which more active pigs are usually healthier than those who are not active, providing farmers with knowledge of identifying pigs\u2019 health state before they become sick or their condition becomes life-threatening. However, the conventional means of estimating pig mobility largely rely on manual observations by farmers, which is impractical in the context of contemporary centralized and extensive pig farming operations. In response to these challenges, multi-object tracking and pig behavior methods are adopted to monitor pig health and welfare closely. Regrettably, these existing methods frequently fall short of providing precise and quantified measurements of movement distance, thereby yielding a rudimentary metric for assessing pig health. This paper proposes a novel approach that integrates optical flow and a multi-object tracking algorithm to more accurately gauge pig movement based on both qualitative and quantitative analyses of the shortcomings of solely relying on tracking algorithms. The optical flow records accurate movement between two consecutive frames and the multi-object tracking algorithm offers individual tracks for each pig. By combining optical flow and the tracking algorithm, our approach can accurately estimate each pig\u2019s movement. Moreover, the incorporation of optical flow affords the capacity to discern partial movements, such as instances where only the pig\u2019s head is in motion while the remainder of its body remains stationary. The experimental results show that the proposed method has superiority over the method of solely using tracking results, i.e., bounding boxes. The reason is that the movement calculated based on bounding boxes is easily affected by the size fluctuation while the optical flow data can avoid these drawbacks and even provide more fine-grained motion information. The virtues inherent in the proposed method culminate in the provision of more accurate and comprehensive information, thus enhancing the efficacy of decision-making and management processes within the realm of pig farming.<\/jats:p>","DOI":"10.3390\/s23239499","type":"journal-article","created":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:34:10Z","timestamp":1701304450000},"page":"9499","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Pig Movement Estimation by Integrating Optical Flow with a Multi-Object Tracking Model"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-2125-6908","authenticated-orcid":false,"given":"Heng","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Electronics and Information Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea"},{"name":"Core Research Institute of Intelligent Robots, Jeonbuk National University, Jeonju 54896, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0001-3355-7898","authenticated-orcid":false,"given":"Seyeon","family":"Chung","sequence":"additional","affiliation":[{"name":"Core Research Institute of Intelligent Robots, Jeonbuk National University, Jeonju 54896, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0003-9963-7430","authenticated-orcid":false,"given":"Junaid Khan","family":"Kakar","sequence":"additional","affiliation":[{"name":"Department of Electronics and Information Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea"},{"name":"Core Research Institute of Intelligent Robots, Jeonbuk National University, Jeonju 54896, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang Cheol","family":"Kim","sequence":"additional","affiliation":[{"name":"Core Research Institute of Intelligent Robots, Jeonbuk National University, Jeonju 54896, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-3321-5695","authenticated-orcid":false,"given":"Hyongsuk","family":"Kim","sequence":"additional","affiliation":[{"name":"Core Research Institute of Intelligent Robots, Jeonbuk National University, Jeonju 54896, Republic of Korea"},{"name":"Department of Electronics Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1037655","DOI":"10.3389\/fpls.2022.1037655","article-title":"Data-centric annotation analysis for plant disease detection: Strategy, consistency, and performance","volume":"13","author":"Dong","year":"2022","journal-title":"Front. 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