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Security

High-quality data labeling for the security industry - from identifying faces in camera footage to creating training data for tracking complex objects.
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Expert Labeling
of Security Data

Security Data Annotation services for a wide range of computer vision applications.
Security Data Annotation
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Security data annotation presents a unique set of challenges and opportunities. Through careful, manual annotation of your visual data, we can create datasets that will teach your AI security system to: recognize individuals, objects, and animals; detect a movement, and track an object through multiple video frames, or even multiple security cameras.

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Security
Annotation Types

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01. Automatic Annotation

Using machine learning for fast and efficient labeling of your security data - our team will validate every image for accuracy.

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Automatic Annotation

02. Bounding Box

Annotate relevant objects in camera footage or images with the help of simple boxes that help keep track of them.

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Bounding Box

03. Oriented Bounding Box

Places objects in security footage at the right angle for additional accuracy during the labeling and training process.

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Oriented Bounding Box

04. Cuboid

Useful for representing data in your security footage in 3D by extrapolating height and width from images of objects.

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Cuboid

05. Polygon

Helps outline irregular shapes for important objects such as specific items people may be carrying.

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Polygon

06. Semantic Segmentation

Catalogs entire scenes in security footage by classifying objects - helps your systems understand complexity.

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Semantic Segmentation

07. Instance Segmentation

An advanced form of segmentation that individually labels every single instance of an object found in your security data.

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Instance Segmentation

08. Skeletal

Uses connected lines to recognize humans in your security data - it helps label their posture, movement style, and so on.

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Skeletal

09. Key Points

Methodically labeling individual parts of someone’s face or specific features to detect emotional state, understand intent, etc.

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Key Points

10. Lane

Label lanes or roads often found in the background of your security footage. Helps train AI to understand scenes better.

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Lane

11. Bitmap

Often used to identify separated parts of the same object in your image or video - often applies to complex scenes with lots of objects.

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Bitmap

12. 3D Point Cloud

Labeling data in entire 3D environments for your security systems to better orient in the real world with full knowledge of distances.

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3D Point Cloud

13. Custom

Combine different types of security data annotation and train your specific AI systems to tackle any tasks they need to.

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Custom

Professional Data Annotation
for Security

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Get accurately labeled data for your computer vision systems in the security industry!

01. Facial Recognition

Developing AI that can precisely recognize faces, read emotions, and understand the health condition of a person has been a challenge for many decades. The quality and variety of training data are key factors in your model performance. Keymakr is at the frontier of creating training data for facial recognition computer vision AI. We have created and perfected methods for creating high-quality large training datasets for:

  • Facial Recognition
  • Emotion Recognition
  • Biometrics

02. Emotion Recognition

We can create and label datasets consisting of millions of images, hundreds of hours of video footage, thousands of fingerprints, or whatever else your project requires. Using state-of-the-art techniques for detecting micro-expressions and the position of facial muscles, we can help your system understand human emotion like never before.

03. Security-Related Applications

Security-Related Applications

We offer powerful tools and techniques to label faces under a variety of conditions. This includes advanced face-matching scenarios, as well as assigning custom data structures to customer-supplied visuals.

  • Image annotation for recognition of weapons or dangerous objects.
  • Image annotation for face recognition.
  • Object or person tagging and tracking through multiple frames.
  • Object classification on security monitors.

04. Recognizing Weapons and Dangerous Objects

Analyzing an enormous amount of visual data from CCTV cameras and identifying dangerous objects in real time could be exhausting (if not impossible) for human operators. That is where AI steps in automated image recognition algorithms can alert operators about anything that requires attention.

We can annotate any type of security imaging data that will teach your system how to react to potentially dangerous situations.

05. Object or Person Tagging and Tracking on Security Monitors

A carefully designed mix of customer and in-house generated data can teach AI to tackle the most complex tag-and-track assignments, whether these are people, animals, or objects traversing multiple fields of view.

AI can effectively analyze continuous streams of visual data to pre-screen and highlight any areas of concern.

06.Custom Datasets Tailored to Your Security Needs

We specify, generate, and validate custom datasets that fine-tune pattern-matching capabilities. This allows AI to assume 90% of visual classification and detection workload, separating human operators from raw image data, reducing staff stress, and alleviating privacy concerns.

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"Delivering Quality and Excellence"

The upside of working with Keymakr is their strategy to annotations. You are given a sample of work to correct before they begin on the big batches. This saves all parties time and...

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"Great service, fair price"

bility to accommodate different and not consistent workflows.
Ability to scale up as well as scale down.
All the data was in the custom format that...

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"Awesome Labeling for ML"

I have worked with Keymakr for about 2 years on several segmentation tasks.
They always provide excellent edge alignment, consistency, and speed...

Meet
Keymakr

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We bring deep hands-on experience with validating, labeling, and creating data to your project so you can focus on what you
do best - developing amazing solutions.

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Keymakr started with a core team of 10 employees in 2015 and grew to employ over 1000 in-house team members in just two years. We are not only helping to create the best AI possible, we are
creating jobs for people that are as passionate as we are about technology.

To achieve this, we created a proprietary data annotation platform that enables us and our partners to provide high-quality clean data to anyone in need of it.

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