Computer Vision: Image and Video Recognition
Farix Machine Learning solution processes large arrays of visual data and automates image and video recognition.
Fayrix offers a wide range of complex software and harware IoT solutions targeted at real estate developers, property management and utility service companies and community associations. The solutions ensure straightforward cooperation workflows, optimize costs and bring transparency to related business procceses. The main features include online service requests creation, payment of bills, utility meter readings submission & utility consumption management, lighting management, ventilation management and Big Data services related to preventive maintenance and operations optimization based on Machine Learning.
Advantages of computer vision
Processing large amounts of data which a human can’t even physically cover.
Continuous operations. A computer does not need breaks to eat and sleep, while processing visual data compared to a human.
High reaction speed. Machine is always working real-time and its only purpose is to do its job.
Flexible methodologies. The solution is customized for particular business needs.
Business process automation
No human mistakes.
Releasing human resource from machine work, payroll costs descrease.
A computer can take into account many more details compared to a human being.
Text & Image recognition
One of the key aspects in computer vision discipline is image recognition.
The main challenge in image recognition is to match particular visual data with some predefined classes. Such technology solutions are essential for various business areas ranging from processing simple digital images to automated interpretation of medical and military devices.
Agriculture
Crop production quality control
Augmented realty
Defining object location based on sensor data
Autonomous vehicles
Spacial orientation, road signs and signals recognition
Biometry
Person identification
How does computer
VISION WORK?
Computer vision project implementation illustrated by solving a problem of hand gesture recognition
Extracting image
Hand/face/object (does the image contain a hand?)
Image preparation
Skin color detection and segmentation (can be adapted to any human phenotype)
Identification of low-level image properties
Collecting picture characteristics
Extracting only meaningful properties of all collected ones
Classfication
Using neural network to recognise the gesture
Exit class
A typical computer vision solution
development and integration
One of the key aspects in computer vision discipline is image recognition.
The main challenge in image recognition is to match particular visual data with some predefined classes. Such technology solutions are essential for various business areas ranging from processing simple digital images to automated interpretation of medical and military devices
