Last updated: 28 February 2025

Animal Behavior Analysis with Deep Learning: Advanced Insights through Machine Vision

Historically, understanding animal behavior has been a meticulous task heavily reliant on human observation. However, the integration of deep learning and machine vision to understand animal behavior has ushered in a new era of efficiency and precision in this field. By harnessing the power of advanced algorithms, researchers can now unlock invaluable insights into animal behaviors, social dynamics, and environmental responses. This article serves as a roadmap, outlining essential steps and solutions for constructing a robust animal behavior analysis system based on deep learning.

Animal Behavior Analysis with Deep Learning: Advanced Insights through Machine Vision

For instance, consider the potential of analyzing pig behavior to understand their emotional states and improve welfare. By tracking subtle movements and facial expressions, researchers can develop AI-powered models to detect signs of stress, pain, or contentment, leading to more humane farming practices. These insights have important implications, from meat quality assessment to overall animal well-being.

By incorporating face analysis techniques, researchers can look deeper into the emotional landscape of animals, making the way for a more compassionate and sustainable approach to livestock management.

Machine vision camera selection

The foundation of any successful animal behavior analysis project is the selection of a suitable camera system. This critical component determines the quality and quantity of data collected, significantly impacting the accuracy and depth of
subsequent analysis. Several key factors must be considered when choosing an industrial camera for animal behavior studies.

 

Resolution is essential for capturing detailed animal behavior. A high-resolution camera enables precise tracking of body movements, facial expressions, and subtle details. For instance, studying the social interactions of primates requires capturing fine-grained information such as hand gestures and eye movements. Our
VEN-505-36U3M-M01 model, with a resolution of 2592x1944 pixels, provides an excellent basis for capturing such information.

 

Frame rate is equally crucial, especially when analyzing fast-paced behaviors. A higher frame rate allows for more accurate tracking of quick movements and ensures that no crucial behavioral moments are missed. While our VEN-505-36U3M-M01 offers a respectable frame rate of 36fps, researchers studying fast-moving animals, such as birds or rodents, might require a camera with an even higher frame rate.

 

Sensitivity is another important factor, particularly in environments with varying lighting conditions. A camera with good low-light performance is crucial for capturing clear images in dim or shaded areas. Monochrome sensors, like the one in our VEN-505-36U3M-M01, generally exhibit higher sensitivity compared to color sensors, making them ideal for low-light
conditions.

Selecting the Optimal Lens

Choosing the right industrial lens is crucial for capturing clear and detailed animal behavior data. The lens significantly impacts image quality, field of view (FOV), and working distance (WD), all of which are essential for accurate analysis.

 

The ideal lens for animal behavior studies depends on various factors, including the size of the animals, the desired level of detail, and the observation environment. For instance, studying small rodents in a laboratory setting might require a macro
lens to capture fine motor skills and facial expressions. In contrast, observing large mammals in their natural habitat might necessitate a telephoto lens to maintain a safe distance while capturing clear images.

  

For example, a 4mm lens with a FOV of 513.2 x 384.9 mm and a WD of 400 mm might be suitable for studying small animals in a controlled environment. This lens offers a wide FOV, allowing researchers to capture a broad range of behaviors within a limited space. The WD of 400 mm provides ample working distance for manipulating experimental setups or observing animals without disturbing them.

 

Additionally, lens distortion can affect the accuracy of behavior analysis. Minimizing distortion is crucial for precise measurements and tracking of animal movements. Wide-angle lenses are often prone to distortion, so researchers should consider using prime lenses or non-distortion lenses.

 

By carefully considering these factors and consulting with imaging experts, researchers can select the optimal lens for their specific animal behavior study, maximizing the quality and utility of their data.

Lighting for Animal Behaviour Analysis

Proper machine vision lighting is crucial for capturing high-quality animal behavior data. Adequate illumination ensures that subtle details, such as facial expressions and body movements, are clearly visible. The choice of lighting depends on various factors, including the size of the animals, the observation environment, and the desired level of detail.

 

For animals that are sensitive to light, such as nocturnal species, infrared (IR) illumination can be a valuable tool. IR light is invisible to humans and many animals, allowing researchers to observe behavior without disturbing the subjects. By using IR cameras and our VA-SWIR-RL and VA-SWIR-BL researchers can capture clear images in low-light conditions.

 

Experimentation with different lighting setups is often necessary to find the optimal balance for specific animal behavior studies. When planning and implementing lighting strategies researchers can ensure that their animal behavior data is of the highest quality, facilitating accurate analysis and interpretation.

VA-SWIR-RL

Applications examples

Animal behavior analysis has a wide range of applications across various fields. Here are some examples:

By studying the behavior of endangered species, researchers can identify threats, develop conservation strategies, and monitor population dynamics.

Analyzing animal behavior can help optimize livestock management, improve animal welfare, and enhance productivity.

Studying animal models can provide insights into human diseases and inform the development of new treatments.

Analyzing animal behavior can contribute to our understanding of social interactions,
learning, and cognition.

Animal behavior analysis can be used to create realistic and engaging animations and video games.

These are just a few examples of how animal behavior analysis can be applied. As technology continues to advance, we can expect to see even more innovative and impactful applications in the future.

Support for Animal Behaviour Analysis vision systems

Would you like to have support from one of our machine vision experts for creating your own Animal Behaviour Analysis system? Or another similar vision system? Don’t hesitate to reach out by using the form below!

Left image description

Max Reijngoudt

Computer vision for quality control and sorting of vegetables / fruits and plants

More and more companies in the agricultural sector are investing in automation, industrial cameras and smart software (AI) are used for optical quality control and sorting of vegetables, fruits and plants.

Read more