A computer vision method for on-line behavioral quantification of individually caged poultry

Transactions of the ASABE

Volumn 49, Issue 3, 2006, Pages 795-802

  Leroy, T ^a   Vranken, E ^a   Van Brecht, A ^a   Struelens, E ^b   Sonck, B ^b   Berckmans, D ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b WALLOON AGRICULTURAL RESEARCH CENTRE   (Belgium)

Author keywords

Animal behavior; Computer vision; Dynamic analysis; Furnished cages; Housing systems; Laying hens; Welfare

Indexed keywords

ANIMAL BEHAVIOR; DYNAMIC ANALYSIS; FURNISHED CAGES; HOUSING SYSTEMS; LAYING HENS; WELFARE;

BIODIVERSITY; CAMERAS; COMPUTER VISION; HEALTH CARE; IMAGE PROCESSING; PHYSIOLOGY;

AGRICULTURE;

ANIMAL WELFARE; BEHAVIORAL RESPONSE; COMPUTER VISION; DYNAMIC ANALYSIS; HEALTH CARE; PHYSIOLOGY; POULTRY;

AGRICULTURE; BIODIVERSITY; CAMERAS; HEALTH; PHYSIOLOGY;

ANIMALIA;

EID: 33748908775     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (31)

1. Abrahamsson, P. 1996. Furnished cages and aviaries for laying hens: Effects on production, health, and use of facilities. Report 234. Uppsala, Sweden: Swedish University of Agricultural Sciences, Department of Animal Nutrition and Management.
2. Aerts, J.-M., D. Berckmans, P. Saevels, E. Decuypere, and J. Buyse. 2000. Dynamic and static responses of total heat production of broiler chickens to step changes in temperature and light intensity. Trans. ASAE 43(6): 1835-1841.
3. Birchfield, S. 1998. Elliptical head tracking using intensity gradients and color histograms. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, 401-406. Piscataway, N.J.: IEEE.
4. Blake, A., and M. Isard. 2000. Active Contours. Berlin, Germany: Springer-Verlag.
5. Bloemen, H., D. Berckmans, J.-M. Aerts, and V. Goedseels. 1997. Image analysis to measure activity of animals. Equine Veterinary J., Suppl. 23: 16-19.
6. Bulpitt, A. J., Boyle, R. D., Forbes, and J. M. 2000. Monitoring behaviour of individuals in crowded scenes. In Proc. 3rd International Conference on Methods and Techniques in Behavioral Research, 28-30. Nijmegen, The Netherlands: Noldus.
7. Chi, Y. T., C. F. Chien, and T. T. Lin. 2003. Leaf shape modeling and analysis using geometric descriptors derived from Bezier curves. Trans. ASAE 46(1): 175-185.
8. Cooles, T., C. Taylor, D. Cooper, and J. Graham. 1995. Active shape models: Their training and application. Computer Vision and Image Understanding 61(1): 38-59.
9. De Wet, L., E. Vranken, A. Chedad, J.-M. Aerts, J. Ceunen, and D. Berckmans. 2003. Computer-assisted image analysis to quantify daily growth rates of broiler chickens. British Poultry Sci. 44(4): 524-532.
10. European Union. 1999. Directive EU/74/1999. Brussels, Belgium: Council of the European Union.
11. Frost, A. R., C. P. Schofield, S. A. Beaulah, T. T. Mottram, J. A. Lines, and C. M. Wathes. 1997. A review of livestock monitoring and the need for integrated systems. Computers and Electronics in Agric. 17(2): 139-159.
12. Kass, M., A. Witkin, and D. Terzopoulos. 1987. Snakes: Active contour models. Intl. J. Computer Vision 1(4): 321-331.
13. Leroy, T., J. Ceunen, E. Struelens, A. Janssen, F. Tuyttens, K. De Baere, J. Zoons, B. Sonck, E. Vranken, and D. Berckmans. 2003a. Developing a real-time computer vision system for the quantification of poultry behaviour in furnished cages. In Abstracts of the 54th Annual Meeting of the European Association for Animal Production, 186. Rome, Italy: European Association for Animal Production.
14. Leroy, T., J. Ceunen, E. Struelens, A. Janssen, F. Tuyttens, K. De Baere, E. Vranken, J. Zoons, B. Sonck, and D. Berckmans. 2003b. Developing a computer vision system for the on-line quantification of the behaviour of laying hens in furnished cages. In Welfare of the Laying Hen, 405. G. C. Perry, ed. Wallingford, U.K.: CABI Publishing.
15. Ljung, L. 1987. System Identification: Theory for the User. Englewood Cliffs, N.J.: Prentice Hall.
16. Ljung, L., and S. T. Soderstrom. 1983. Theory and Practice of Recursive Identification. Cambridge, Mass.: MIT Press.
17. Minagawaha, H., and T. Ichikawa. 1994. Determining the weight of pigs with image analysis. Trans. ASAE 37(3): 1011-1015.
18. Norton, J. 1986. An Introduction to Identification. London, U.K.: Academic Press.
19. Quanten, S., P. McKenna, A. Van Brecht, A. Van Hirtum, P. C. Young, K. Janssens, and D. Berckmans. 2003. Model-based PIP control of the spatial temperature distribution in cars. Int. J. Control 76(16): 1628-1634.
20. Sergeant, D. M., R. D. Boyle, and J. M. Forbes. 1998. Computer visual tracking of poultry. Computers and Electronics in Agric. 21(1): 1-18.
21. Shao, J., H. Xin, and J. D. Harmon. 1997. Neural network analysis of postural behavior of young swine to determine the IR thermal comfort state. Trans. ASAE 40(3): 755-760.
22. Tao, Y., and J. Walker. 2000. Imaging and pattern recognition methods for feather sex separation of broiler chicks. Trans. ASAE 43(2): 461-467.
23. Twining, C. J., C. J. Taylor, and P. Courtney. 2000. Robust tracking and posture description for laboratory rodents using active shape models. Behavior Res. Methods Instruments and Computers 33(3): 381-391.
24. Van der Stuyft, E., C. P. Schofield, J. M. Randall, P. Wambacq, and V. Goedseels. 1991. Development and application of computer vision systems for use in livestock production. Computers and Electronics in Agric. 6(3): 243-265.
25. Wang, C. L., and P. C. Young. 1988. Direct digital control by input output state variable feedback: Theoretical background. Int. J. Control 31(4): 741-764.
26. Xin, H. 1999. Assessing swine thermal comfort by image analysis of postural behaviors. J. Animal Sci. 77(suppl. 2): 1-7.
27. Ying, Y., H. Jing, Y. Tao, and N. Zhang. 2003. Detecting stem and shape of pears using Fourier transformation and an artificial neural network. Trans. ASAE 46(1): 157-162.
28. Young, P. C. 1984. Recursive Parameter Estimation and Time Series Analysis: An Introduction. Berlin, Germany: Springer-Verlag.
29. Young, P. C., and A. Jakeman. 1979. Refined instrumental variable methods of recursive time series analysis: 1. Single input, single output systems. Int. J. Control 29(1): 1-30.
30. Young, P. C., and A. Jakeman. 1980. Refined instrumental variable methods of recursive time series analysis: 3. Extension. Int. J. Control 31(4): 741-764.
31. Zhong, Y., A. K. Jain, and M. P. Dubuisson-Jolly. 2000. Object tracking using deformable templates. IEEE Trans. Pattern Analysis and Machine Intelligence 22(5): 544-549.