Document type : Article published in Pig Progress
Author: Suresh Neethirajan
Preview: Humans can communicate by speaking, writing or gesturing and also have faces that usually portray how they feel. What if the emotions of farm animals could also be interpreted accurately through their communication, faces and body language? An effort to do just this is being made at Wageningen University & Research in the Netherlands. […]
What if an animal's face could be read like a human's? A sensor capable of detecting all the variances of animal faces has not yet been developed. In the interim, a variety of sensors are used to measure various components and parables. Such tools incorporate infrared thermal imaging, sound recordings, GPS tracking and drones. However, none of these are totally satisfactory by themselves and they all have their individual shortcomings in data collection. The quest is on among scientists to find a sensor that detects the smallest facial tick. In turn, such observable movements will be matched to what the animal is feeling at the time. […]
To have accurate facial recognition is mandatory as, like humans, animals have their individual levels of stress and must be evaluated separately and by species. So far, results of animals are from controlled environments, such as a farm, without a comparative measurement or benchmark of free range or wild animals. Some kind of baseline must be used to measure animal emotions by species in their natural environment, but such data is currently unavailable due to a lack of any suitable monitoring equipment. […]
Computer programmes, like WUR Wolf, developed by the Farmworx group in the Netherlands' Wageningen University & Research, analysed animal facial features. The programme recognises and evaluates 14 facial features combinations and seven emotional states of cows and pigs. For the study, images and videos of several thousand pigs and dairy cows were evaluated using You Only Look Once (YOLO) real time object detection. The corresponding data was interpreted by PyCharm and Python computer programming languages. The deep learning model WUR Wolf was dedicated in identifying facial expressions of these farm animals, successfully identifying 86% of the animals and their emotional states. A spinoff industry from this could be for the many security applications on the farm and elsewhere.
WUR Wolf identifies animal emotions based on four principal facial expressions - neutral, aggression, happiness and fear. To build a database, the test sample of pigs was used to determine the correct algorithm. A number of artificial intelligence (AI) algorithms and camera and infrared imaging systems were used to gather data, such as eye retinal detection and the complex simulation of a neural network, to produce an automated emotion evaluation from what might be called a thinking computer. Such technology has previously been used for human aids to produce interactive robots, in the advertising industry to determine consumer preferences, and as an education tool, to name a few.
