3D imaging and body measurement of riding horses using four scanners simultaneously
Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported methods with a single scanner still face a significant challenge: the time necessary for scanning is too long for the horses to remain stationary....
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Published in | Journal of Equine Science Vol. 35; no. 1; pp. 1 - 7 |
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Format | Journal Article |
Language | English |
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Japan
Japanese Society of Equine Science
2024
Japan Science and Technology Agency The Japanese Society of Equine Science |
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Abstract | Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported methods with a single scanner still face a significant challenge: the time necessary for scanning is too long for the horses to remain stationary. This study attempted to scan the horse simultaneously from four directions using four scanners in order to complete the scans in a short amount of time and then combine the images from the four scans on a computer into one whole image of each horse. This study also compared body measurements from the combined 3D images with those taken from conventional manual measurements. Nine riding horses were used to construct stereoscopic composite images, and the following 10 measurements were taken: height at the withers, back, and croup; chest depth; width of the chest (WCh), croup, and waist; girth circumference, cannon circumference (CaC), and body length. The same 10 measurements were taken by conventional manual methods. Relative errors ranged from −1.89% to 7.05%. The correlation coefficient between manual and 3D measurements was significant for all body measurements (P<0.01) except for WCh and CaC. A simple regression analysis of all body measurements revealed a strong correlation (P<0.001, R2=0.9994, root-mean-square error=1.612). Simultaneous scanning with four devices from four directions reduced the scanning time from 60 sec with one device to 15 sec. This made it possible to perform non-contact body measurements even on incompletely trained horses who could not remain stationary for long periods of time. |
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AbstractList | Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported methods with a single scanner still face a significant challenge: the time necessary for scanning is too long for the horses to remain stationary. This study attempted to scan the horse simultaneously from four directions using four scanners in order to complete the scans in a short amount of time and then combine the images from the four scans on a computer into one whole image of each horse. This study also compared body measurements from the combined 3D images with those taken from conventional manual measurements. Nine riding horses were used to construct stereoscopic composite images, and the following 10 measurements were taken: height at the withers, back, and croup; chest depth; width of the chest (WCh), croup, and waist; girth circumference, cannon circumference (CaC), and body length. The same 10 measurements were taken by conventional manual methods. Relative errors ranged from -1.89% to 7.05%. The correlation coefficient between manual and 3D measurements was significant for all body measurements (P<0.01) except for WCh and CaC. A simple regression analysis of all body measurements revealed a strong correlation (P<0.001, R2=0.9994, root-mean-square error=1.612). Simultaneous scanning with four devices from four directions reduced the scanning time from 60 sec with one device to 15 sec. This made it possible to perform non-contact body measurements even on incompletely trained horses who could not remain stationary for long periods of time.Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported methods with a single scanner still face a significant challenge: the time necessary for scanning is too long for the horses to remain stationary. This study attempted to scan the horse simultaneously from four directions using four scanners in order to complete the scans in a short amount of time and then combine the images from the four scans on a computer into one whole image of each horse. This study also compared body measurements from the combined 3D images with those taken from conventional manual measurements. Nine riding horses were used to construct stereoscopic composite images, and the following 10 measurements were taken: height at the withers, back, and croup; chest depth; width of the chest (WCh), croup, and waist; girth circumference, cannon circumference (CaC), and body length. The same 10 measurements were taken by conventional manual methods. Relative errors ranged from -1.89% to 7.05%. The correlation coefficient between manual and 3D measurements was significant for all body measurements (P<0.01) except for WCh and CaC. A simple regression analysis of all body measurements revealed a strong correlation (P<0.001, R2=0.9994, root-mean-square error=1.612). Simultaneous scanning with four devices from four directions reduced the scanning time from 60 sec with one device to 15 sec. This made it possible to perform non-contact body measurements even on incompletely trained horses who could not remain stationary for long periods of time. Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported methods with a single scanner still face a significant challenge: the time necessary for scanning is too long for the horses to remain stationary. This study attempted to scan the horse simultaneously from four directions using four scanners in order to complete the scans in a short amount of time and then combine the images from the four scans on a computer into one whole image of each horse. This study also compared body measurements from the combined 3D images with those taken from conventional manual measurements. Nine riding horses were used to construct stereoscopic composite images, and the following 10 measurements were taken: height at the withers, back, and croup; chest depth; width of the chest (WCh), croup, and waist; girth circumference, cannon circumference (CaC), and body length. The same 10 measurements were taken by conventional manual methods. Relative errors ranged from -1.89% to 7.05%. The correlation coefficient between manual and 3D measurements was significant for all body measurements (P<0.01) except for WCh and CaC. A simple regression analysis of all body measurements revealed a strong correlation (P<0.001, R =0.9994, root-mean-square error=1.612). Simultaneous scanning with four devices from four directions reduced the scanning time from 60 sec with one device to 15 sec. This made it possible to perform non-contact body measurements even on incompletely trained horses who could not remain stationary for long periods of time. Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported methods with a single scanner still face a significant challenge: the time necessary for scanning is too long for the horses to remain stationary. This study attempted to scan the horse simultaneously from four directions using four scanners in order to complete the scans in a short amount of time and then combine the images from the four scans on a computer into one whole image of each horse. This study also compared body measurements from the combined 3D images with those taken from conventional manual measurements. Nine riding horses were used to construct stereoscopic composite images, and the following 10 measurements were taken: height at the withers, back, and croup; chest depth; width of the chest (WCh), croup, and waist; girth circumference, cannon circumference (CaC), and body length. The same 10 measurements were taken by conventional manual methods. Relative errors ranged from −1.89% to 7.05%. The correlation coefficient between manual and 3D measurements was significant for all body measurements (P<0.01) except for WCh and CaC. A simple regression analysis of all body measurements revealed a strong correlation (P<0.001, R 2 =0.9994, root-mean-square error=1.612). Simultaneous scanning with four devices from four directions reduced the scanning time from 60 sec with one device to 15 sec. This made it possible to perform non-contact body measurements even on incompletely trained horses who could not remain stationary for long periods of time. Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported methods with a single scanner still face a significant challenge: the time necessary for scanning is too long for the horses to remain stationary. This study attempted to scan the horse simultaneously from four directions using four scanners in order to complete the scans in a short amount of time and then combine the images from the four scans on a computer into one whole image of each horse. This study also compared body measurements from the combined 3D images with those taken from conventional manual measurements. Nine riding horses were used to construct stereoscopic composite images, and the following 10 measurements were taken: height at the withers, back, and croup; chest depth; width of the chest (WCh), croup, and waist; girth circumference, cannon circumference (CaC), and body length. The same 10 measurements were taken by conventional manual methods. Relative errors ranged from −1.89% to 7.05%. The correlation coefficient between manual and 3D measurements was significant for all body measurements (P<0.01) except for WCh and CaC. A simple regression analysis of all body measurements revealed a strong correlation (P<0.001, R2=0.9994, root-mean-square error=1.612). Simultaneous scanning with four devices from four directions reduced the scanning time from 60 sec with one device to 15 sec. This made it possible to perform non-contact body measurements even on incompletely trained horses who could not remain stationary for long periods of time. |
ArticleNumber | JES2311 |
Author | TORII, Suzuka OJIMA, Yuki KIKU, Yoshio MATSUURA, Akihiro |
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Cites_doi | 10.1136/vr.125.22.549 10.3390/s19225046 10.1016/S0140-6736(86)90837-8 10.1016/j.compag.2019.01.019 10.1016/j.jevs.2015.02.005 10.3390/s18093014 10.1016/j.jevs.2011.05.002 10.1016/j.compag.2022.106987 10.3168/jds.2014-8969 10.1294/jes.32.73 10.1590/0103-8478cr20160590 10.1016/j.jevs.2013.01.002 10.1111/j.2042-3306.1988.tb01451.x 10.1016/j.jevs.2019.04.008 10.2527/jas.2013-6689 10.1016/j.compag.2020.105510 |
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References | 6. Hoffmann, G., Bentke, A., Rose-Meierhöfer, S., Ammon, C., Mazetti, P., and Hardarson, G.H. 2013. Estimation of the body weight of Icelandic horses. J. Equine Vet. Sci. 33: 893–895. 10. Li, J., Ma, W., Li, Q., Zhao, C., Tulpan, D., Yang, S., Ding, L., Gao, R., Yu, L., and Wang, Z. 2022. Multi-view real-time acquisition and 3D reconstruction of point clouds for beef cattle. Comput Electron Agric 197: 106987. 15. Pérez-Ruiz, M., Tarrat-Martín, D., Sánchez-Guerrero, M.J., and Valera, M. 2020. Advances in horse morphometric measurements using LiDAR. Comput. Electron. Agric. 174: 105510. 8. Huang, L., Guo, H., Rao, Q., Hou, Z., Li, S., Qiu, S., Fan, X., and Wang, H. 2019. Body dimension measurements of Qinchuan cattle with transfer learning from LiDAR sensing. Sensors (Basel) 19: 5046. 2. Carroll, C.L., and Huntington, P.J. 1988. Body condition scoring and weight estimation of horses. Equine Vet. J. 20: 41–45. 11. Martinson, K.L., Coleman, R.C., Rendahl, A.K., Fang, Z., and McCue, M.E. 2014. Estimation of body weight and development of a body weight score for adult equids using morphometric measurements. J. Anim. Sci. 92: 2230–2238. 17. Wagner, E.L., and Tyler, P.J. 2011. A comparison of weight estimation methods in adult horses. J. Equine Vet. Sci. 31: 706–710. 3. Catalano, D.N., Coleman, R.J., Hathaway, M.R., Neu, A.E., Wagner, E.L., Tyler, P.J., McCue, M.E., and Martinson, K.L. 2019. Estimation of actual and ideal bodyweight using morphometric measurements of miniature, saddle-type, and Thoroughbred horses. J. Equine Vet. Sci. 78: 117–122. 7. Huang, L., Li, S., Zhu, A., Fan, X., Zhang, C., and Wang, H. 2018. Non-contact body measurement for Qinchuan cattle with LiDAR sensor. Sensors (Basel) 18: 3014. 16. Vieira, P.S., Nogueira, C.E.W., Santos, A.C., Borba, L.D.A., Scalco, R., Brasil, C.L., Barros, W.S., and Curcio, B.D.R. 2017. Development of a weight-estimation model to use in pregnant criollo-type mares. Cienc. Rural 48: e20160590. 1. Bland, J.M., and Altman, D.G. 1986. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327: 307–310. 4. Le Cozler, Y., Allain, C., Caillot, A., Delouard, J.M., Delattre, L., Luginbuhl, T., and Faverdin, P. 2019. High-precision scanning system for complete 3D cow body shape imaging and analysis of morphological traits. Comput. Electron. Agric. 157: 447–453. 9. Jones, R.S., Lawrence, T.L.J., Veevers, A., Cleave, N., and Hall, J. 1989. Accuracy of prediction of the liveweight of horses from body measurements. Vet. Rec. 125: 549–553. 12. Matsuura, A., Dan, M., Hirano, A., Kiku, Y., Torii, S., and Morita, S. 2021. Body measurement of riding horses with a versatile tablet-type 3D scanning device. J. Equine Sci. 32: 73–80. 13. Murray, J.M.D., Bloxham, C., Kulifay, J., Stevenson, A., and Roberts, J. 2015. Equine nutrition: a survey of perceptions and practices of horse owners undertaking a massive open online course in equine nutrition. J. Equine Vet. Sci. 35: 510–517. 14. Oki, H., and Nagata, Y. 1983. A study on growth on 24 body parts in the Thoroughbred. Bull. Epuine Res.Inst. 20: 16–26. 5. Fischer, A., Luginbühl, T., Delattre, L., Delouard, J.M., and Faverdin, P. 2015. Rear shape in 3 dimensions summarized by principal component analysis is a good predictor of body condition score in Holstein dairy cows. J. Dairy Sci. 98: 4465–4476. 11 12 13 14 15 16 17 1 2 3 4 5 6 7 8 9 10 |
References_xml | – reference: 6. Hoffmann, G., Bentke, A., Rose-Meierhöfer, S., Ammon, C., Mazetti, P., and Hardarson, G.H. 2013. Estimation of the body weight of Icelandic horses. J. Equine Vet. Sci. 33: 893–895. – reference: 1. Bland, J.M., and Altman, D.G. 1986. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327: 307–310. – reference: 4. Le Cozler, Y., Allain, C., Caillot, A., Delouard, J.M., Delattre, L., Luginbuhl, T., and Faverdin, P. 2019. High-precision scanning system for complete 3D cow body shape imaging and analysis of morphological traits. Comput. Electron. Agric. 157: 447–453. – reference: 12. Matsuura, A., Dan, M., Hirano, A., Kiku, Y., Torii, S., and Morita, S. 2021. Body measurement of riding horses with a versatile tablet-type 3D scanning device. J. Equine Sci. 32: 73–80. – reference: 8. Huang, L., Guo, H., Rao, Q., Hou, Z., Li, S., Qiu, S., Fan, X., and Wang, H. 2019. Body dimension measurements of Qinchuan cattle with transfer learning from LiDAR sensing. Sensors (Basel) 19: 5046. – reference: 5. Fischer, A., Luginbühl, T., Delattre, L., Delouard, J.M., and Faverdin, P. 2015. Rear shape in 3 dimensions summarized by principal component analysis is a good predictor of body condition score in Holstein dairy cows. J. Dairy Sci. 98: 4465–4476. – reference: 9. Jones, R.S., Lawrence, T.L.J., Veevers, A., Cleave, N., and Hall, J. 1989. Accuracy of prediction of the liveweight of horses from body measurements. Vet. Rec. 125: 549–553. – reference: 16. Vieira, P.S., Nogueira, C.E.W., Santos, A.C., Borba, L.D.A., Scalco, R., Brasil, C.L., Barros, W.S., and Curcio, B.D.R. 2017. Development of a weight-estimation model to use in pregnant criollo-type mares. Cienc. Rural 48: e20160590. – reference: 2. Carroll, C.L., and Huntington, P.J. 1988. Body condition scoring and weight estimation of horses. Equine Vet. J. 20: 41–45. – reference: 7. Huang, L., Li, S., Zhu, A., Fan, X., Zhang, C., and Wang, H. 2018. Non-contact body measurement for Qinchuan cattle with LiDAR sensor. Sensors (Basel) 18: 3014. – reference: 17. Wagner, E.L., and Tyler, P.J. 2011. A comparison of weight estimation methods in adult horses. J. Equine Vet. Sci. 31: 706–710. – reference: 10. Li, J., Ma, W., Li, Q., Zhao, C., Tulpan, D., Yang, S., Ding, L., Gao, R., Yu, L., and Wang, Z. 2022. Multi-view real-time acquisition and 3D reconstruction of point clouds for beef cattle. Comput Electron Agric 197: 106987. – reference: 11. Martinson, K.L., Coleman, R.C., Rendahl, A.K., Fang, Z., and McCue, M.E. 2014. Estimation of body weight and development of a body weight score for adult equids using morphometric measurements. J. Anim. Sci. 92: 2230–2238. – reference: 14. Oki, H., and Nagata, Y. 1983. A study on growth on 24 body parts in the Thoroughbred. Bull. Epuine Res.Inst. 20: 16–26. – reference: 15. Pérez-Ruiz, M., Tarrat-Martín, D., Sánchez-Guerrero, M.J., and Valera, M. 2020. Advances in horse morphometric measurements using LiDAR. Comput. Electron. Agric. 174: 105510. – reference: 13. Murray, J.M.D., Bloxham, C., Kulifay, J., Stevenson, A., and Roberts, J. 2015. Equine nutrition: a survey of perceptions and practices of horse owners undertaking a massive open online course in equine nutrition. J. Equine Vet. Sci. 35: 510–517. – reference: 3. Catalano, D.N., Coleman, R.J., Hathaway, M.R., Neu, A.E., Wagner, E.L., Tyler, P.J., McCue, M.E., and Martinson, K.L. 2019. Estimation of actual and ideal bodyweight using morphometric measurements of miniature, saddle-type, and Thoroughbred horses. J. Equine Vet. Sci. 78: 117–122. – ident: 9 doi: 10.1136/vr.125.22.549 – ident: 8 doi: 10.3390/s19225046 – ident: 1 doi: 10.1016/S0140-6736(86)90837-8 – ident: 4 doi: 10.1016/j.compag.2019.01.019 – ident: 13 doi: 10.1016/j.jevs.2015.02.005 – ident: 7 doi: 10.3390/s18093014 – ident: 14 – ident: 17 doi: 10.1016/j.jevs.2011.05.002 – ident: 10 doi: 10.1016/j.compag.2022.106987 – ident: 5 doi: 10.3168/jds.2014-8969 – ident: 12 doi: 10.1294/jes.32.73 – ident: 16 doi: 10.1590/0103-8478cr20160590 – ident: 6 doi: 10.1016/j.jevs.2013.01.002 – ident: 2 doi: 10.1111/j.2042-3306.1988.tb01451.x – ident: 3 doi: 10.1016/j.jevs.2019.04.008 – ident: 11 doi: 10.2527/jas.2013-6689 – ident: 15 doi: 10.1016/j.compag.2020.105510 |
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Snippet | Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported... Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported... |
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SubjectTerms | Body length body measurement Body measurements Body size Chest composite stereoscopic image conformation Correlation coefficient Correlation coefficients Croup Error analysis horse Horses Regression analysis Scanners Scanning Stereoscopy Three dimensional composites three-dimensional scan Time measurement |
Title | 3D imaging and body measurement of riding horses using four scanners simultaneously |
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