Image motion feature extraction for recognition of aggressive behaviors among group-housed pigs

- Only aggressive pigs were located and key frame sequences were extracted.
- The two aggressive pigs were considered as a whole rectangle.
- The acceleration of this rectangle was extracted as the feature.
- The acceleration feature was used for recognition of aggressive behaviors.
- The acceleration details in each frame were presented.

The aim of this study is to develop a computer vision-based method to automatically detect aggressive behaviors among pigs. Ten repetitions of the same experiment were performed. In each of the experiment, 7 piglets were mixed from three litters in two pigpens and captured on video for a total of 6 h. From these videos, the first 3 h of video after mixing were recorded as a training set, and the 3 h of video after 24 h were recorded as a validation set. Connected area and adhesion index were used to locate aggressive pigs and to extract key frame sequences. The two pigs in aggression were regarded as a whole rectangle according to their characteristics of continuous and large-proportion adhesion. The acceleration feature was extracted by analyzing the displacement change of four sides of this rectangle between adjacent frames, and hierarchical clustering was used to calculate its threshold. Based on this feature, the recognition rules of medium and high aggression were designed. Testing 10 groups of pigs, the accuracy of recognizing medium aggression was 95.82% with a sensitivity of 90.57% and with a specificity of 96.95%, and the accuracy of recognizing high aggression was 97.04% with a sensitivity of 92.54% and with a specificity of 97.38%. These results indicate that the acceleration can be used to recognize pigs' aggressive behaviors.