What Is That - Computer Vision?
Computer Vision is an interdisciplinary science that deals with the theory and technology of creating machines and software that can detect, track and classify different objects using video cameras. It studies the development of computer methods and systems capable of intelligently perceiving the world of images and video, as close as possible to human perception.
The scope of Сomputer Vision is very wide: from bar code readers in supermarkets to augmented reality. Along with Machine Learning, Computer Vision is one of the main directions in the development of artificial intelligence systems.
If the red eyes in Terminator represented a nightmarish future, now they are a new round of technology.
Computer Vision Technologies in The Most Common Application Areas:
- 1. Any system in which intellectual analysis of visual information is required;
- 2. Production sector/Industry (flaw detection, quality control, industrial robots), car manufacturing, electronic engineering, mechanical engineering, space technology;
- 3. Medicine (automatic analysis of medical images – X-ray, tomography, ultrasonography);
- 4. Human-computer interface based on gestures and facial expressions;
- 5. Object management systems based on visual information analysis;
- 6. Security systems (person identification, motion detectors, recognition and tracking of moving objects, recognition of car numbers, etc.);
- 7. Recognition systems for handwritten or printed text, and image reconstruction;
- 8. Systems for creating 3D models using 3D and 2D video cameras;
- 9. Video compression based on the contents of the video stream (content-aware video compression);
- 10. Games and multimedia applications.
The diagram below shows the areas of Computer Vision in
which our experts have a really rich experience
Static Image Analysis
- Face recognation and identification
- Raster image tracing and convertion into vector images
- Object analysis and identification
- Optical charter recognation
- Pattern/Images recognation
Motion Analysis
- Motion detection
- Motion objects tracking, recognation and identification
- Motion trajectory prediction
- Action scenaries based on motion detection and recognation
Video Stream Recognation
- Face recognation and identification
- Charter recognation in video stream
- Rules based objects and area monitoring
- Production process monitoring and control
- 3D reconstruction from frames sequence
- Computer vision based control and management system
3D Cameras Video Recognation
- Scenario-based production area monitoring and process control
- Product/objects volume measurement
- Objects recognation and identification
Augmented and Virtual Reality
- Interactive 3D simulators
- Visualisation and modeling of process for interaction with user
- Visualisation of production areas with data received from computer vision system
Our Team Experience and Theoretical Background
High-level Computer Vision requires 1st-class specialists.
Our team consists of specialists with 10+ years of experience in this growing sphere.
For this time they have published more than 100+ scientific articles and articles in the field of computer vision.
We use different methods for pattern recognition
and image processing
- Image Normalization (automatic compensation of geometric transformation including projection transformation)
- Tracking Normalization – methods that allow tracking of moving objects and various information for object management and recognition
- Neural Networks
- Segmentation algorithms
- Moving detection based on differences in images
- Objects recognition based on neural networks, correlations, partial correlations, and points of interest
- Moving detection based on differences in images
- Histograms analysis
- Cluster analysis
- Differential equations, integrals, mathematical morphology, numerical methods including our own solutions used for image processing
- Skeleton Building Methods
- Machine Learning algorithms
- Realization of algorithms for working in real-time applications
How Cool The Completed Projects Can Be
Manufacturing and security
С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Tracking of moving objects, predicting the movement trajectory and providing alarms in certain cases;
- Calculating the objects volume, and in case that these objects are homogeneous, the weight of the object can be calculated;
- With the help of neural networks, it is possible to recognize the type of the object and to calculate its number;
- Measurement of the objects size possible in the system;
Healthcare security
С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Face search in a video stream and face search in a photo database;
- Multi-threaded search from many video sources and cameras;
- Integral and local recognition methods: PCA, ICA, FLD, LFA, Fisher effects, hidden Markov models, and
cluster analysis. Facial Actions Code System (FACS) and Neural Networks were implemented in the system; - Extraction of deformations and movements methods: Point Distributions Model (PDM) system was
implemented; - Geometrical characteristics and appearance characteristics methods to identify a specific set of
emotions were used.
Manufacturing and healthcare
С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Analysis and identification of the object, counting the number, size and shape of objects;
- Clinker quality analysis with the recognition of its structure and identity of the object’s form and
size; - Identifying an object in images;
- Raster image tracing and conversion into vector images;
- Cluster analysis for finding similar photos.
Manufacturing and sport
С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Monitoring and control of moving parts of different objects in real-time;
- Collection of information about particular coordinates of some parts of objects from the video stream
received from the camera; - Systems can check the state of some mechanical systems, movements of people and gestures in real-time;
- Measure the coordinates of the necessary fragments or parts of the required objects and save the
collected information for future analysis or generate the necessary actions depending on the specific
needs of the system; - The system uses neural networks to process information from the video stream;
- Requires minimal interaction with the user only on the first stage for defining fragments in a video
stream with objects from which information should be gathered; - Service Execution – on the appointed day it is only necessary to come and receive the necessary
treatment.
Manufacturing
С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Building 3D model of objects based on video from camera;
- Calculating the objects volume, and in case that these objects are homogeneous, the weight of the object
can be calculated; - With the help of neural networks, it is possible to recognize the type of the object and to calculate
its number; - Measurement of the objects size possible in the system;
-
Complex video surveillance system for video stream analysis
Complex video surveillance system for video stream analysisSolutions:Manufacturing and security
Technologies:С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Tracking of moving objects, predicting the movement trajectory and providing alarms in certain cases;
- Calculating the objects volume, and in case that these objects are homogeneous, the weight of the object can be calculated;
- With the help of neural networks, it is possible to recognize the type of the object and to calculate its number;
- Measurement of the objects size possible in the system;
-
Faces and emotions recognition and identification system
Faces and emotions recognition and identification systemSolutions:Healthcare security
Technologies:С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Face search in a video stream and face search in a photo database;
- Multi-threaded search from many video sources and cameras;
- Integral and local recognition methods: PCA, ICA, FLD, LFA, Fisher effects, hidden Markov models, and
cluster analysis. Facial Actions Code System (FACS) and Neural Networks were implemented in the system; - Extraction of deformations and movements methods: Point Distributions Model (PDM) system was
implemented; - Geometrical characteristics and appearance characteristics methods to identify a specific set of
emotions were used.
-
System for analysis of images gathered under microscope
System for analysis of images gathered under microscopeSolutions:Manufacturing and healthcare
Technologies:С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Analysis and identification of the object, counting the number, size and shape of objects;
- Clinker quality analysis with the recognition of its structure and identity of the object’s form and
size; - Identifying an object in images;
- Raster image tracing and conversion into vector images;
- Cluster analysis for finding similar photos.
-
System for tracking and gathering parameters of moving parts in observed objects
System for tracking and gathering parameters of moving parts in observed objectsSolutions:Manufacturing and sport
Technologies:С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Monitoring and control of moving parts of different objects in real-time;
- Collection of information about particular coordinates of some parts of objects from the video stream
received from the camera; - Systems can check the state of some mechanical systems, movements of people and gestures in real-time;
- Measure the coordinates of the necessary fragments or parts of the required objects and save the
collected information for future analysis or generate the necessary actions depending on the specific
needs of the system; - The system uses neural networks to process information from the video stream;
- Requires minimal interaction with the user only on the first stage for defining fragments in a video
stream with objects from which information should be gathered; - Service Execution – on the appointed day it is only necessary to come and receive the necessary
treatment.
-
System for identification of volume, size, amount, and weight of various products
System for identification of volume, size, amount, and weight of various productsSolutions:Manufacturing
Technologies:С++, Java, PostgreSQL, AWS, Bluemix, Azure, OpenCV, Dlib, own algorithms. OS: Windows, Linux
- Building 3D model of objects based on video from camera;
- Calculating the objects volume, and in case that these objects are homogeneous, the weight of the object
can be calculated; - With the help of neural networks, it is possible to recognize the type of the object and to calculate
its number; - Measurement of the objects size possible in the system;
As a microchip in the system, small bonus about the future of Computer Vision
Computer Vision has several main applications-drivers of growth.
- Robotics, including autonomous driving systems, which everyone now talks about. Robotics has always been the main patroness of Computer Vision, an area where its capabilities and results have been most in demand.
- Systems connected with the Internet and with the so-called Big Data. The main players in the field of Computer Vision are large corporations, such as Google and Facebook, who need to process, understand, recognize, index a huge number of images, a billion or even tens of billions a day.
- Physicians and scientists. They have more and more images but not enough time to analyse all of them.
- Entertainment industry: computer games, virtual reality, augmented reality.
- And, of course, video surveillance systems, biometrics, face recognition and so on – everything related to the Big Brother. But here we must emphasize that the applications associated with the Big Brother are only a small part of the application of Computer Vision.
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