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

Fangfang Xue; Yueming Wang; Qi Li

doi:10.3788/LOP202158.2215007

Journals >Laser & Optoelectronics Progress >Volume 58 >Issue 22 >Page 2215007 > Article

Laser & Optoelectronics Progress
Vol. 58, Issue 22, 2215007 (2021)

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

Fangfang Xue, Yueming Wang, and Qi Li^*

Author Affiliations

School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, China

show less

DOI: 10.3788/LOP202158.2215007 Cite this Article Set citation alerts

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 Copy Citation Text

show less

Fig. 1. Schematic diagram of the technical solution

Download full size

Fig. 2. Structure diagram of the YOLOv5s model

Download full size

Fig. 3. Schematic diagram of the angle between feature parts

Download full size

Fig. 4. Structure of the fully connected neural network

Download full size

Fig. 5. Labeling of feature parts

Download full size

Fig. 6. Training results of the YOLOv5s model. (a) Loss curve; (b) precision; (c) recall; (d) mAP

Download full size

Fig. 7. Detection results of cattle feature parts

Download full size

Fig. 8. Sample image of the cattle behavior. (a) Standing behavior; (b) lying behavior; (c) feeding behavior

Download full size

Fig. 9. Training curve of the fully connected neural network model. (a) Loss curve; (b) accuracy curve

Download full size

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 1. Vector format of feature part spatial relationship

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 2. Training accuracy of the YOLOv5s 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 3. Classification accuracy of fully connected neural network 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 4. Classification accuracy of decision tree model unit: %

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

Table 5. Statistics of cattle behavior time

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

Download Citation

Set citation alerts for the article

Tools

Set citation alerts for the article

Save the article for my favorites

Paper Information