Camera Check Service
Camera Check Service
3DiVi Inc., founded in 2011, is one of the leading developers of AI and machine learning (ML) technologies for computer vision.
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Omni Face Recognition Platform
An integrable face recognition system for analyzing images and video
Omni Face Recognition Platform
An integrable face recognition system for analyzing images and video
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Face detection and tracking in images and video
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Face comparison and search in control lists with a face match score
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Face identification at different angles and tilts
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Identification of masked or partially covered faces
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Confident detection with 20 px between pupils and identification with 30 px
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Face liveness detection (spoofing) and photo suitability check for identification (QAA)
Face Recognition System for Large-Scale Projects
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50 million face vector comparisons per second
Searching through a database of 50 million faces using 1 CPU core takes 1 second -
½ second for face vector creation and database search
Image search takes ½ second for single requests and supports linear scalability up to X requests per second with horizontal server scaling -
Unlimited number of faces in the database
Creation and storage of a database of people (over 100,000,000) with face photos, full names, activity history, and additional free-form text fields -
Adding cameras without expanding the system core
For video analytics tasks, there is no need to buy a central server with extra power for future scaling, as adding cameras only requires adding video analytics servers -
Unlimited number of cameras or video files
Support for various camera types (IP / USB) and simultaneous multi-threaded processing of camera groups -
External database for storing large images
Delivered in Docker containers and deployed using Kubernetes in a local environment with the possibility of using an external database
Smooth Integration into Access Control and Video Analytics Systems
- GraphQL API and Admin web interfaceMicroservice architecture with GraphQL API via webhook and websocket
Web interface streamlines learning and configuration of key parameters - Existing integrations with video surveillance and access control systemsPartnership integrations with 4 video surveillance systems and 2 access control systems
Versatile and Adaptable Face Recognition Solution
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Support for Ubuntu and CentOS
Deployment support on Ubuntu 20 and CentOS 7. Video processing client can be deployed on Windows and Linux ARM - On-prem installation in an isolated environmentDelivered in Docker containers and deployed using Kubernetes in a local environment
- Deployment in Amazon EKS and Google KE cloud environmentsDeployment in Amazon EKS and Google KE environments with automatic scaling of hardware resources
- Edge processing — recognition without sending video to the centerEdge video stream processing prevents network congestion from high-resolution video streams
- Neural network suite optimized for low-power devicesOption to choose between full and optimized identification methods for mobile and low-power devices
- Protection against photo and data leakage from the databaseWith edge processing, face recognition is performed without sending video to the center, using only face templates without additional information, eliminating the risk of photo leakage
We accompany you through all 4 stages
Market analysis
Share our experience in similar business cases and highlight potentially risky areas.
Offer proven partnership solutions.
Solution selection
Assist in selecting the most suitable technological solutions and propose optimal architecture and equipment configuration.
Provide services for server capacity calculation and assessment of existing cameras' suitability.
Provide testing methodologies for effective participation in pilots.
Implementation and testing
Develop new functionality according to your requirements and ensure quick technical support through various communication channels, including messengers and email.
Conduct an assessment of the quality of face images in the database to predict the probability of identification errors and help configure system parameters to minimize errors.
Market entry
Implement the system under your brand (White Label) to simplify its promotion in the international market.
Offer a flexible licensing model or business model: profit-sharing, transaction-based, or based on the number of faces or cameras.
Services
Documentation
Support
Services
Documentation
- CPU: 4+ cores 3GHz AVX support
- RAM: 24 GB
- HDD: 100 GB
Supported OS versions
System requirements
Performance metrics
Technical Support
Testimonials
Save your development team's time and budget
3DiVi's experience shows that integrating a ready-made face recognition system into your product is 4 times faster and 10 times more cost-effective than developing your own system using SDK.
This also eliminates the risk of inefficient organization of multithreaded processing in your project.
This also eliminates the risk of inefficient organization of multithreaded processing in your project.
Mike P
Project manager
$0 + 2-3 weeks — Testing and exploration
3DiVi provides a server for cloud tests, consultations, and testing materials.
Client engages employees to study the technology for 2-3 weeks.
Client engages employees to study the technology for 2-3 weeks.
Developing your own face recognition solution using SDK:
Required team (6-9 people):
architect, developers, analyst, QA, technical writer, manager.
Fast response from SDK providers is required.
architect, developers, analyst, QA, technical writer, manager.
- 3-5 months — developing image processing functionality.
- 4-6 months — developing video stream processing functionality.
- 3-4 months — process debugging, test development, bug fixing.
- 2-3 months — optimization for different platforms and hardware.
Fast response from SDK providers is required.
$9 500 + 2-3 months — PoC / MVP level integration
3DiVi provides a devpack with the necessary set of licenses for a year, helps deploy and configure the system for the business task, and offers technical support. Devpack costs can be refunded as a discount when purchasing licenses for a real project.
Client purchases the devpack, hardware (own or in AWS/GKE cloud), cameras, and engages their developers for product integration for 2-3 months.
Client purchases the devpack, hardware (own or in AWS/GKE cloud), cameras, and engages their developers for product integration for 2-3 months.
$25 000 + 3-5 months — Product level integration
3DiVi provides a devpack with the necessary set of licenses for a year, helps deploy and configure the system for the business task, offers technical support, and customizes the system for specific integration requirements. Devpack costs can be refunded as a discount when purchasing licenses for a real project or ordering new functionality.
Client purchases the devpack, hardware (own or in AWS/GKE cloud), cameras, and engages their developers for product integration for 3-5 months.
Client purchases the devpack, hardware (own or in AWS/GKE cloud), cameras, and engages their developers for product integration for 3-5 months.
$200 000 — MVP / PoC level