Recognition of Cattle Daily Behavior Based on Spatial Relationship of Feature Parts

No.	Characteristics value meaning
1--3	width of the target box of cattle, body and head (cattle_w, body_w, head_w)
4--6	height of the target box of cattle, body and head (cattle_h, body_h, head_h)
7	distance from head to tail (headtotail_dis)
8--18	distance from head to joint, knee and hoof (headtojoint_dis1-3, headtoknee_dis1-4, headtohoof_dis1-4)
19--29	distance from tail to joint, knee and hoof (tailtojoint_dis1-3, tailtoknee_dis1-4, tailtohoof_dis1-4)
30--40	angle between the head and joint, knee, and hoof relative to the tail (head-tail-joint_ang1-3, head-tail-knee_ang1-4, head-tail-hoof_ang1-4)
41--51	angle between the tail and joint, knee and hoof relative to the head (tail- head-joint_ang1-3, tail- head-knee_ang1-4, tail- head-hoof_ang1-4)

Table 2. Training accuracy of the YOLOv5s model unit: %
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Table 2. Training accuracy of the YOLOv5s model unit: %
Recognition category mAP Cattle Body Head Tail Joint Hoof Knee
AP 90.9 94.0 94.9 97.2 87.7 84.4 91.1 87.2

Table 3. Classification accuracy of fully connected neural network model unit: %
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Table 3. Classification accuracy of fully connected neural network model unit: %
Standardized processing Dropout processing All behavior Standing Lying Feeding
× × 96.2 96.8 96.2 95.3
× √ 96.7 96.4 98.7 90.6
√ × 97.2 97.2 98.7 95.3
√ √ 97.7 97.6 100 95.3

Table 4. Classification accuracy of decision tree model unit: %
View table
Table 4. Classification accuracy of decision tree model unit: %
Standardized processing All behavior Standing Lying Feeding
× 91.9 91.7 93.6 90.6
√ 96.7 97.6 96.2 93.8

Table 5. Statistics of cattle behavior time
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Table 5. Statistics of cattle behavior time
Behavior Standing Lying Feeding
Real time /s 232.1 262.4 88.3
Predicted time /s 238.0 262.0 83.0
Relative error /% 2.54 -0.15 -6.00

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Fangfang Xue, Yueming Wang, Qi Li. Recognition of Cattle Daily Behavior Based on Spatial Relationship of Feature Parts[J]. Laser & Optoelectronics Progress, 2021, 58(22): 2215007

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