Computer Vision Services and Custom Solutions

Hire us to develop custom computer vision models leveraging our experience when you need it.

computer vision services

Computer Vision Services

Computer Vision Services

Leveraging visual information in the era of data explosion is made possible and profitable via the expert use of AI. Here at Mindtitan, we develop Computer Vision applications focused on deriving meaningful information from visual inputs like images and videos at a scale and speed impossible for humans. Our experience in this domain allows us to provide our partners with solutions tailored to their specific datasets, scale and performance needs.

Image Recognition

Image Recognition

Image recognition is tasked with detecting and identifying people, items, places, writing or otherwise specific features on an image. Vision data like pictures from different manufacturing steps in a production line, for instance, could be used to make real-time decisions based on real-time detections of any quality or process deviation in real-time.

Historical data could also be batch processed to gain insight on the current production procedure to seek continuous improvement.

We can provide vision systems that can be leveraged across multiple fields by leveraging different tools: in addition to the classification models described above, we can use Image Segmentation methods that are used to divide (segment) each image in multiple areas so that each pixel belongs to a known label.

Object Detection

Object Detection  

Object detection adds localization to the former family of models by providing exact information regarding the position of multiple objects within the images. The application field for these models is extremely varied and includes, for example:

  • Detection of production issues or defects in manufacturing
  • Automation of visual inspections of equipment or buildings
  • Warehousing automation and inventory assessments
  • Characterising different production stages in the pharmaceutical industry
  • Crowd counting in public spaces as well as tools to guarantee that a minimum distance is respected when required
  • Workplace safety/PPE monitoring tools

Optical character recognition models convert images of typed, handwritten or printed text into machine-encoded text and are used for translation services, licence plate recognition and road-side signage information extraction.

Face Recognition

Face Recognition

Our services also include ad-hoc AI systems like Face Recognition models that match known pictures of individuals to new images even when partial occlusion or angle variations are present.

Using distinctive facial features like the distance between the eyes or the shape of the cheekbones, the algorithms produce a condensed representation of the detected face for easy comparison against a database.

Such capability can be used for:

  • access control to restricted areas
  • assist law enforcement in identifying criminals and missing persons, even among crowds
  • identity validation in a purchase process
Video Analytics

Video Analytics

Moving from image to Video Analytics, we can leverage additional information to a series of images (frames in a video) by taking into account the features that are relevant across multiple frames.

Video Recognition

Video Recognition

Video inputs can provide supplementary information in subsequent images such as a new angle/view of an object or the evolution of a person’s motion. We can translate this extra data into a deeper knowledge and insight through video processing algorithms that are at the core of functionalities like:

  • Human Activity Recognition tools can be used to assess what activities a person is carrying out and are used in security systems, sport and health surveillance, medical and disability assistance, gaming and human-computer interaction, retail theft prevention.
  • Visual speech recognition
  • Facial and micro expressions recognition
Object Tracking

Object Tracking

Going further from video classification, Object tracking models leverage the change in object localization of the detected labels over different video frames enabling technologies like

  • Autonomous driving, which at its core consists of an “awareness” of the vehicle position compared to others and the road.
  • Gaze estimation to quantitatively measure human engagement and intention
  • Speed estimation

Computer vision use cases

Computer vision use cases
image recognition

Image Recognition

  • Analysis of satellite, aerial/drone, remote sensing or hyperspectral imaging for land cover detection, environment conservation, livestock monitoring, urban or agricultural development
  • Medical diagnosis and prediction via x-ray, EKG and MRI imaging processing
  • Safety monitoring systems that analyse body scanner/metal detector imaging in correctional facilities to detect smuggling.
object detection

Object Detection

  • Detection of production issues or defects in manufacturing
  • Automation of visual inspections of equipment or buildings
  • Warehousing automation and inventory assessments
  • Characterising different production stages in the pharmaceutical industry
  • Crowd counting in public spaces as well as tools to guarantee that a minimum distance is respected when required
  • Workplace safety/PPE monitoring tools
face recognition

Face Recognition

Such capability can be used for:

– access control to restricted areas

– assist law enforcement in identifying criminals and missing persons, even among crowds

– identity validation in a purchase process

Video Recognition

  • Human Activity Recognition tools can be used to assess what activities a person is carrying out and are used in security systems, sport and health surveillance, medical and disability assistance, gaming and human-computer interaction, retail theft prevention.
  • Visual speech recognition
  • Facial and micro expressions recognition
object tracking

Object Tracking

  • Autonomous driving, which at its core consists of an “awareness” of the vehicle position compared to others and the road.
  • Gaze estimation to quantitatively measure human engagement and intention
  • Speed estimation

How we work?

How we work?
Mapping the problem
automated customer service

Mapping the problem

Working closely with your company, we will identify the key areas where AI can bring the most value. This involves meetings with all stakeholders and developing a roadmap for action together.

Data exploration and proof of concept
testimonial fuzu

Data exploration and proof of concept

We will evaluate if you have the business data needed to train relevant machine learning models. If required, we identify additional frameworks for data collection in your company.

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Proposal for deliverables
meeting

Proposal for deliverables

Based on our meetings and data analysis, we’ll share with you the possible AI use cases for your company. We will work hand-in-hand to agree on the desired outcome.

Model development
how do chatbots work

Model development

We will build and apply various machine learning models to your business data, to find the best solution. As a result, we will develop algorithms that accomplish the desired goal

Application deployment
call analysis

Application deployment

We integrate the machine learning model with an API or front-end product, making it user-friendly and accessible to the end-user.

Maintenance
model development

Maintenance

Any system might require time to time maintenance, and we are happy to support our customers with that.

Frequently asked questions

Frequently asked questions
How do I know that you can solve my problem with Computer vision?

In general, if a decision or choice needs to be made based on visual medium features, if a human can do it, then a machine can do it. It just becomes a question of how much data is available for training and how much effort is required to build the models necessary to achieve the business goals.

 

Who is responsible for data collection and labelling?

Data collection is most often on the client/SME side, as it is connected to the peculiar business problem to be solved. Labeling can be on the client side if very specific knowledge is required for labeling or it can be outsourced to us or a labeling company. Hybrid solutions are also available and in all cases, we provide proper labeling training and guidelines tailored to the computer vision task.

How long does it take to execute a Computer Vision project?

If you imagine the process made up of iterations of the cycle: data collection, labeling, model development + training, testing & evaluation and deployment into the customer solution, usually the first 2 steps take 20-50% of the time (the smaller the project / standard problem, the higher the percentage) while the split between the latter 3 is really dependent of the novelty of the problem being solved, the required performance level and the complexity of deployment. The computer vision project range is from 3 months to multi-year collaborations.

Do you guarantee the success of the project?

During the project evaluation, we provide a feasibility assessment and, for problems in which we have experience, we can provide a more precise prediction at the level of the computer vision metrics and discuss the forecasted minimum level of performance.

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konstantin sadekov mindtitan