Apply Machine Learning to Increase Safety & Security
Better computer vision for surveillance tasks involving biometrics, facial recognition, crowd counting, & more
Machine Learning for Retail, Workplace Safety, Face Recognition, & Crowd Counting
Ensure safety by detecting threats by deploying pipelines to processing video, image, and audio data from your security cameras, as well data from multispectral sensors. From shoplifting to identifying persons of interest - mitigate risks before they escalate
Car detection & license plate recognition
Rapidly deploy solutions to count the number of cars in a given parking lot or detect the entry of unauthorized vehicles
Use deep learning to abandoned luggage in airports, detect weapons, aggressive behavior in the office, or keep workers safe from slip and fall hazards
Biometrics & facial recognition
Use biometrics such as facial landmarks or voice patterns to ensure security in public and private spaces. Prevent security breaches with deepfake detection models
Crowd counting & person search
Design computer vision-powered products to find people to find individuals across real-time surveillance camera feeds & count crowds
Retail & in-store experience
Improve your store layout, understand shopper satisfaction & flow within the store, or build a self-checkout solution
Detect baby cries, screams, sirens, breaking glass, or loud bangs. Develop urban sound monitoring solutions for smart cities
Theft and loss prevention
Train models to prevent theft of valuables, home break-ins or shoplifting, and help catch perpetrators on the spot
Machine Learning Datasets for Face Recognition & Security
Don't have proprietary data? Get a head start by using one of the public machine learning datasets for surveillance. Browse datasets for facial recogntion, sound detection, crowd counting, license plate recognition & car detection
- Explore action recognition &
surveillance datasets ...
- ... detect cars & pedestrians,
recognize license plates ...
- ... or conduct face recognition,
person search, & count crowds!
Lights, camera, action recognition. Data infrastructure for security camera feeds is no longer a time thief with Activeloop
Computer vision brings scalability to safety & security thanks to surveillance camera data
In the safety & security space, computer vision comes to help in a large variety of initiatives, which typically include real-time processing of large amounts of data from sound or motion detectors, as well as surveillance cameras. The advances in machine learning help prevent theft in stores, improve shoppers' retail experience, detect cars, recognize car license plates or faces, count crowds, or identify individuals via biometrics.
With Activeloop, machine learning teams working on surveillance & safety tasks are able to build scalable data infrastructure to connect their live surveillance feeds to their machine learning models. Moreover, data scientists can collaborate on curating their datasets by visualizing individual slices with our rapid query engine. Finally, materialized data can be streamed while training machine learning models - regardless if data is stored locally or on the cloud.