Cow behavior recognition based on image analysis and activities
Abstract
Keywords: cow behavior, target segmentation, image entropy, image moment, activities, intelligent analysis
DOI: 10.3965/j.ijabe.20171003.3080
Citation: Gu J Q, Wang Z H, Gao R H, Wu H R. Cow behavior recognition based on image analysis and activities. Int J Agric & Biol Eng, 2017; 10(3): 165–174.
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Mu C, Xie J, Yan W, Liu T, Li P. A fast recognition algorithm for suspicious behavior in high definition videos. Multimedia Systems, 2016; 22(3): 275–285.
Borchers M R, Chang Y M, Tsai I C, Wadsworth B A, Bewley J M. A validation of technologies monitoring dairy cow feeding, ruminating, and lying behaviors. Journal of Dairy Science, 2016; 99(9): 7458–7466.
María B, Marta M, Jorge L A. Behavioral effects in adolescence and early adulthood in two length models of maternal separation in male rats. Behavioural Brain Research, 2017; 324: 77–86.
Rekik K, Francés B, Valet P, Dray C, Florian C. Cognitive deficit in hippocampal-dependent tasks in Werner syndrome mouse model. Behavioural Brain Research, 2017; 323: 68–77.
Devanne M, Berretti S, Pala P, Wannous H, Daoudi M,Bimbo A D. Motion segment decomposition of RGB-D sequences for human behavior understanding. Pattern Recognition, 2017; 61: 222–233.
Salau J, Haas J H, Thaller G, Leisen M, Junge W. Developing a multi-Kinect-system for monitoring in dairy cows: object recognition and surface analysis using wavelets. Animal, 2016; 10(9): 1–12.
Wenigera M, Kappa F, Friederichsa P. Spatial verification using wavelet transforms: a review. Quarterly Journal of the Royal Meteorological Society, 2016.
Firk R, Stamer E, Junge W, Krieter J. Automation of
oestrus detection in dairy cows: a review. Livestock Production Science, 2002; 75(3): 219–232.
Batchuluun G, Kim Y G, Kim J H, Hong H G, Park K R. Robust behavior recognition in intelligent surveillance environments. Sensors, 2016; 16(7):1010.
Oh S, Pandey M, Kim I, Hoogs A. Image-oriented economic perspective on user behavior in multimedia social forums. Pattern Recognition Letters, 2016; 72(C): 33–40.
Zissis D, Xidias E K, Lekkas D. Real-time vessel behavior prediction. Evolving Systems, 2016; 7(1): 29–40.
Palacio S, Bergeron R, Lachance S, Vasseur E. The effects of providing portable shade at pasture on dairy cow behavior and physiology. Journal of Dairy Science, 2015; 98(9): 6085–6093.
Sawalhah M N, Cibils A F, Maladi A, Cao H, Vanleeuwen D M. Forage and weather Influence day versus nighttime cow behavior and calf weaning weights on rangeland. Rangeland Ecology & Management, 2016; 69(2): 134–143.
Porto S M C, Arcidiacono C, Anguzza U, Cascone G. The automatic detection of dairy cow feeding and standing behaviours in free-stall barns by a computer vision-based system. Biosystems Engineering, 2015; 133: 46–55.
Servedio M R. The effects of predator learning, forgetting, and recognition errors on the evolution of warning coloration. Evolution, 2015; 54(3): 751–763.
Nilsson M, Herlin A H, Ardö H, Guzhva O, Åström K, Bergsten C. Development of automatic surveillance of animal behaviour and welfare using image analysis and machine learned segmentation technique. Animal, 2015; 9(11): 1859–1865.
Cattelan M, Varin C. Hybrid pairwise likelihood analysis of animal behavior experiments. Biometrics, 2013; 69(4): 1002–1011.
Leroy T, Vranken E. A computer vision method for on-line behavioral quantification of individually caged poultry. Transactions of the ASABE, 2006; 49(3): 795–802
Egnor S E, Branson K. Computational analysis of behavior. Annual Review of Neuroscience, 2016; 39(1): 217.
Balch T, Khan Z, Veloso M. Automatically tracking and analyzing the behavior of live insect colonies. AGENTS’01, 2001; pp.521–528.
Shao B, Xin H W. A real-time computer vision assessment and control of the thermal comfort for group-housed pigs. Computer and Electronics in Agriculture, 2008; 62(2): 15–21.
Lao F, Du X D, Teng G H. Automatic recognition method of laying hen behaviors based on depth Image processing. Transactions of the CSAM, 2017; 48(1): 155–162. (in Chinese)
Wang J, Chen X J, Chang L Q, Fang D Y, Xing T Z, Nie W
K.. Compressive sensing based device-free moving target trajectory depiction. Chinese Journal of Computers, 2014; 37(74): 1–15. (in Chinese)
Ji B, Zhu W X, Liu B, Li X, Ma C. Video analysis for tachypnea of pigs based on fluctuating ridge-abdomen. Transactions of the CSAE, 2011; 27(1): 191–195. (in Chinese)
Liu B, Zhu W X, Yang J J, Ma C H. Extracting of pig gait frequency feature based on depth image and pig skeleton endpoints analysis. Transactions of the CSAE, 2014; 30(10): 131–137. (in Chinese)
Zhu W X, Pu X F, Li X C, Lu C F. Automatic identification system of pigs with suspected case based on behavior monitoring. Transactions of the CSAE, 2010; 26(1): 188–192. (in Chinese)
Duan Y, Li D l, Li Z b, Fu Z T. Review on visual attributes measurement research of aquatic animals based on computer vision. Transactions of the CSAE, 2015; 31(15): 1–11. (in Chinese)
Pang C, He D J, Li C Y, Huang C, Zheng L P. Method of traceability information acquisition and transmission for dairy cattle based on integrating of RFID and WSN. Transactions of the CSAE, 2011; 27(9): 147–152. (in Chinese)
He D J, Meng F C, Zhao K X, Zhang Z. Recognition of calf basic behaviors based on video analysis. Transactions of the CSAM, 2016; 47(9): 294–300. (in Chinese)
Tian F Y, Wang R R, Liu M C, Wang Z, Li F D, Wang Z H. Oestrus detection and prediction in dairy cows based on neural networks. Transactions of the CSAM, 2013; 44(10): 277–281. (in Chinese)
Wen C J, Wang S S, Zhao X, Wang M, Ma L, Liu Y T. Visual dictionary for cows sow behavior recognition. Transactions of the CSAM, 2014; 45(1): 266–274. (in Chinese)
Stem U, He R, Yang C H. Analyzing animal behavior via classifying each video frame using convolutional neural networks. Scientific Reforts, 2015; 5: 1–13
Shen M X, Liu L S, Yan L. Review of monitoring technology for animal individual in animal husbandry. Transactions of the CSAM, 2014; 45(10): 245–251. (in Chinese)
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