Animal and wildlife detection using CVEDIA-RT

Deep learning powered by synthetic data

CVEDIA | Wildlife Animal DetectorCVEDIA | Wildlife Animal DetectorCVEDIA | Wildlife Animal DetectorCVEDIA | Wildlife Animal DetectorCVEDIA | Wildlife Animal DetectorCVEDIA | Wildlife Animal Detector

What is animal detection using deep learning

Animal detection is the ability to find wildlife or pets in photos or video footage. Traditionally people have used computer vision techniques like motion detection to detect animals. However this came with the downside of many false alarms and drained batteries of wildlife cameras. Deep learning significantly reduced those problems as well as enabling the ability to classify animal species. This is important for tracking specific animals in the wild or alerting people to the presence of a pest or predator.


False alarm reduction for perimeter security

It's common for animals to cause false alarms in security and surveillance systems. Especially if they are based only on motion detection. This causes needless alerts and potential alarm fatigue for the operators.

Our animal detector helps by either detecting wildlife using deep learning or by filtering existing alarms using an animal classifier. Which means you can reduce your false alarms to an absolute minimum.

Advanced Driver Assistance Systems (ADAS)

Alerting a driver to animals on the road can save lifes. Often a driver only has a split second to avoid a collision. ADAS systems help by scanning the road ahead to detect any animals that might walk into traffic. Because many animals are active early in the morning or late at night it's better to pair this with our thermal animal detector.

Combined our animal detectors cover multiple spectrums. Which means they work on RGB, near-infrared and thermal cameras. Letting you detect animals in any light condition.

Classifying animal species

Animal detectors point out if there is an animal, and if so, where it is located in your video. Afterwards another AI model classifies the detection to tell you what species or type of animal it's looking at. This means you can track, record or census specific animals saving on battery life and reducing data transfers.

Because classification networks require a lot of data to train, they can be difficult to develop with real data. Especially when dealing with rare animals it's hard to collect enough footage. Our AI models are trained using synthetic data which means we can classify any animal, even if there is no training data available.

Smart homes and invasive animals

Smart home security cameras and doorbells are common in many households. While they are mostly used for detecting people they can also be used for detecting animals. For example to check if a family pet is inside and notify when it wanders outside. Or to alert when there is dangerous wildlife in a backyard.



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