Pet Facial Recognition: Are We There Already?

Technology that can accurately recognize animals will help owners find lost pets, farmers monitor their livestock, and researchers study wild animals. There are several possibilities for this, with microchips being the most popular identification method for pets.

However, implanting chips requires invasive surgery. They cannot be read without a specialized device, and thieves can extract microchips if necessary. Another approach is DNA analysis, which is accurate, but also very expensive and time-consuming.

Pet facial recognition with computer vision software

Pet facial recognition powered by computer vision solutions can be a viable alternative to the above methods. Although it has its drawbacks, the technology can demonstrate a high level of accuracy in specific circumstances.

So how does facial recognition for pets work? And what are the challenges hindering advances in technology?

How does pet face recognition work?

In general, facial recognition solutions for pets work in three main steps:

Image capture: the photo of an animal is taken by a high resolution camera. Some algorithms only work with predefined poses, so it is necessary to select images that meet these criteria. Feature extraction: An animal's biometric data is evaluated for relevance and pre-processing is applied if necessary. Then, the algorithm extracts all the characteristics necessary for recognition. Matching: Extracted features are represented mathematically and compared to other images. For example, if we search for a dog in the lost pets database, we compare the dog's unique characteristics to all animals in that database.

There are several ways to perform a match. One approach is to cluster using algorithms, such as KNN and DBSCAN, which will result in a set of images very close to our target image, and users can manually select the most suitable image.

In addition, probabilistic methods can be deployed to represent the final results as confidence levels. For example, an algorithm may determine that the captured image is a cat with 90% confidence and it is a dog with 10% confidence.

animal face recognition

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Examples of Pet Facial Recognition

Here are examples of how animal facial recognition can be used in real life. Some of these systems are successful, popular, and even commercial solutions, while others are academic attempts to test hypotheses.

Find lost animals

Losing their pets is heartbreaking for owners. And based on the grueling statistics, such incidents are more common than you might think. In the United States, one in three domestic dogs and cats goes missing at some point in their life, and 80% of them are never found. There are several initiatives focused on facial recognition of pets to help owners find their lost friends.

For the legs

This pet facial recognition solution identifies dogs based on the tip of their nose, skin color and fur type. Owners must upload at least three photos to create their pet's profile. Currently, this solution can identify 130 dog breeds with an accuracy rate of 90%.

Seed

This pet recognition company has developed an app that allows pet owners to register and upload photos of their pets. The system analyzes their unique facial features. If owners can provide additional information, such as sex, height and weight, PiP says it will be able to recognize every lost cat and dog.

Anyone who finds a lost pet can use the app to search for owners. PiP's solution also continuously scans social media for animal posts and sends missing animal alerts to local residents...