Computer vision

Automate processes, leverage innovation and deliver better customer experiences with Luxoft’s computer vision services. We deliver value-driven solutions powered by a unique combination of our cutting-edge machine learning and 3D graphics engineering expertise.



Our computer vision services


Object detection and analysis


Detect and manipulate 3D objects to streamline and speed up footage and image editing. Computer vision can automate removing background, manipulating shadows and more for videos with both dynamic and static backgrounds.

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Dashcam footage analysis


Power autonomous driving features or automate dashcam video analytics to speed up insurance claim processing with Luxoft’s computer vision services. Leverage computer vision to automatically detect weather conditions, road signs and more on-demand or in real time.

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Monitoring camera analysis


Ensure your premises are secure, detect shoplifting and theft, and improve customer experience with real-time CCTV security camera footage analytics. Computer vision will detect specific activity and/or object status (e.g., empty shelves).

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Face recognition


Get a fully optimized neural network for face detection and recognition with our computer vision development services. Computer vision can power real-time driver identification and status monitoring, as well as enhance security and enforce restricted access to premises.

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See how computer vision works for yourself

Detecting the scene and weather from the dashcam footage: Interactive case study

Our computer vision solution features


● Support for all H/W platforms and frameworks used by AI/ML ecosystems

● Cutting-edge CI/CD, MLOps and test automation best practices

● Cloud-agnostic deployment for Azure, AWS, GCP and hybrid solutions

● High-quality, up-to-date online documentation and tutorials


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Get a computer vision solution optimized for top-notch performance and accuracy with Luxoft

Why choose Luxoft for computer vision development?


Luxoft's computer vision expertise in numbers


graphics and machine learning professionals


completed projects


success rate

Our toolkit





News and insights

ML/AI algorithms for room layout editing


ML/AI algorithms for room layout editing

Machine learning with Microsoft Azure Monitoring machine learning models in production


Machine learning with Microsoft Azure Monitoring machine learning models in production

Mastering MLOps practices for a trading bot


Mastering MLOps practices for a trading bot


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Supercharge your operational efficiency with Luxoft’s computer vision expertise



Computer vision is a technology that uses artificial intelligence and machine learning to detect specific objects or activities and derive information from video footage and images. A computer vision algorithm can be trained to detect road signs, analyze weather conditions, or classify images, for example.

A computer vision model requires large datasets of labeled videos or images to identify the patterns and rules that it will later use to fulfill its purpose.

For instance, to recognize a crack in a wall, a computer vision algorithm has to be fed a large dataset of images of walls with and without cracks. The algorithm will then “learn” the difference between a wall with and without cracks.

Here are the ten practical applications of computer vision across industries:

  • Identifying weather conditions in the dashcam footage
  • Using facial recognition for authorization and security purposes
  • Enabling autonomous driving by analyzing the road: recognizing road signs, detecting lane markers and potholes, identifying pedestrians
  • Analyzing security camera footage in real time (e.g., detecting when doors open or close)
  • Detecting defects in items on the production line in real time
  • Monitoring livestock behavior and identifying animals with potential health problems
  • Automating UI interface testing
  • Assessing and updating parking lot occupancy in real time
  • Analyzing traffic flow using CCTV footage
  • Detecting queues in retail stores and notifying staff that new checkouts should be open once a threshold is reached

Here are four examples of how computer vision is transforming retail:

  • No-checkout retail. Instead of manually scanning barcodes at the checkout, customers can pick up items while a computer vision solution identifies every object using camera footage
  • Inventory management. Computer vision solutions can detect inventory gaps in real time by identifying empty shelves or misplaced items. They can also be trained to detect damaged packaging or incorrect pricing
  • Store layout. Computer vision can power heat mapping of the store layout, assigning a specific color to each area based on foot traffic. Such heat maps allow the enterprise to better understand customer behavior and improve store layout accordingly
  • Virtual mirrors. Virtual mirrors demonstrate how an item of apparel or accessory would look on the customer without them having to try it on. They are made possible by a combination of computer vision and augmented reality technologies