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Vehicle access control

Vehicle detection and classification

Vehicle detection and classification is performed for moving and static objects in the scene. The algorithm can separate these traffic subjects like: 
cars, busses, trucksbikes.

Also, it is possible to estimate color, model and movement direction for the detected Vehicle. Based on vehicle detection and image processing algorithms it is possible to construct different user defined scenarios and models.

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ALPR

License plate recognition

Automated license plate recognition (ALPR) allows to read vehicle’s registration numbers after detecting them. The algorithm can process videos from traffic cameras and read license plates from multiple moving vehicles at the same time. This solution can bring it’s value for different government and commercial projects.

We are capable to recognize either standard or square license plates.

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Parking space detection

Automated free parking spaces recognition

Automated free parking spaces recognition (AFPSR) is organized via Vehicles smart tracking algorithms using mathematical and geometric algorithms. The main value of our solution is, that it is capable to perform within even not structured environment. That’s mean that it is not needed to lave visible parking slots or borders to use the system.

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Vehicle access control

Automated access control systems based on vehicles and license plates detection.

The combination of Vehicles smart tracking and license plate recognition (ALPR) modules bringing us to a new layer of traffic analyses and control. Automated access control system is created to automate access control for commercial parking, governmental and commercial needs. Billing module and reporting is a powerful part of our solution. Within this solution we also considering integration of our software with existing security and access control hardware.

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Persons’ detection

Detecting people within a photo or video stream.

Human detection and tracking are tasks of computer vision systems for locating and following people in video imagery. Human detection is the task of locating all instances of human beings present in an image, and it has been most widely accomplished by searching all locations in the image, at all possible scales, and comparing a small area at each location with known templates or patterns of people. Human tracking is the process of temporally associating the human detections within a video sequence to generate persistent paths, or trajectories, of the people. Human detection and tracking are generally considered the first two processes in a video surveillance pipeline, and can feed into higher-level reasoning modules such as action recognition and dynamic scene analysis.

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Persons’ tracking and counting

A number of surveillance scenarios require the detection and tracking of people.

People tracking and counting is widely used in different industries starting from security based solutions finishing with marketing aspects. Our flexible solution allows us to segment video-frames and images and to define any custom scenario for people tracking and counting within the frame. User friendly and easy interface will guide you to our features and you will explore all our features without any difficulties.

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Crowd counting

Dense and Sparse Crowd Counting Methods and Techniques

Crowd counting is a technique to estimate the number of people in an image or a video. There are too many people crammed in images and videos sometimes which makes it a huge task for our brain to accurately predict the right number. One quick solution is to start counting the people from the bottom-left, and go one by one but you are sure to lose track and miss the count some time in the middle. This task seems rather not human solvable. However, a machine can do it. Just feed the logic to it, and it pops-up with the precise count.

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Facial identification

Proposed solution is developed with NIST certified modules and guidelines.

A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. Here are the main steps that our system performs to handle with this issue:

  • Detection (eyes, face, key points, landmarks)
  • Normalisation (color conversion enhancement, filtering and registration)
  • Representation (binary patterns, key point descriptors, orientation histograms, wavelets)
  • Extraction (clustering, normalisation, subspace learning, quantisation)
  • Matching (classifiers, density estimation, distance metrics, regressors)

Our solution provides following features:

  • Face recognition
  • Age estimation
  • Gender estimation

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Customized solutions

Proposed solution is developed with NIST certified modules and guidelines.

Our company is always open to hear customers and improve owned solutions with new functionality and design. There are different business needs and custom cases all over the world and VitruviSoft team is ready to dive into different problems to discover the best solution for its customer.

All our components and modules can easily be combined and modified under a specific business model.

Contact us to discuss your needs and explain your business model to be automated.

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