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Hire OpenCV C++ Face Detection Developers

However, the demand for OpenCV developers is growing at a very slow rate, but still, there is sufficient demand for OpenCV C++ face detection developers and programmers in the application development sector. The OpenCV face detection C++ developers are extensively used in modern applications commonly for device authentication and other similar kinds of image recognition applications. The other major domains where the OpenCV C++ face detection developers are extensively used include the following:

OpenCV C++ Face Detection Developer

With many subdomains, artificial intelligence (AI) is one of the major fields where OpenCV face detection C++ engineer, coder or programmer is extensively employed in the present-day industry. While exploring the cutting-edge realm of OpenCV C++ for face detection, integrating Unity developers for hire into your team can significantly enhance the development of interactive and visually rich applications.

OpenCV is a powerful library of different kinds of programming functions, which are used for computer vision in real-time computing. This library was originally created by Intel Corporation about 17 years back in 2000; now it is managed by ItSeez. The official website is Opencv.org.

The latest version (OpenCV 3.4) was released in December 2017. This entire library is written in C/C++ languages and supports APIs for multiple languages and platforms, such as C++, Java, Ruby, Python, Matlab, C#, Perl, Linux, Windows, OpenBSD, FreeBSD, Android, iOS, macOS, Blackberry and others. At present, the demand for face detection OpenCV Unity development team is increasing in 2D and 3D technologies for face detection imaging.

Demand in Different Countries

According to the predictive information about the face detection market in the Allied Market Research Report, the global market value of face detection – 3D and 2D face detection and facial analytics – will cross $9.6 billion by 2022. The market will grow at a robust growth of over 21.3% CAGR during the period 2016 through 2022.

The demand is consistently increasing in all countries across the globe, but North America is the center of this growth where the demand of face detection OpenCV C++ programmer, coder, or engineer will remain very high during the next few years. The Asia Pacific countries like Australia, Japan and China are other major countries where the growth is phenomenal due to extensive use of facial recognition technology into their government and security systems, according to the Markets and Markets Report information.

Based on different research reports, if we draw the average percentile growth in demand for facial recognition in terms of countries, we will have this chart.

The major factor driving this demand of OpenCV C++ face detection developers is increased demand in 2D and 3D face detection domain. Similarly, thermal image sensing is also one of the important factors that have a substantial influence on the market demand of OpenCV C++ face detection programmers.

Countries like Brazil, India, Korea and other major European countries are also driving the demand of OpenCV C++ face detection developer market. According to the information on the Learn OpenCV website, the main reasons for consistent growth in the demand of OpenCV C++ developers include the huge optimized library, no charge or fee required, support for multiple platforms and powerful community to support online. The OpenCV and C++ combination works best for the software production environment to develop high end artificial intelligent applications and services for different domains of businesses.

Anticipated Growth in OpenCV Developers’ Demand

According to the statistics on the IT JOBS WATCH website for the past three years, the growth in the demand for face detection OpenCV C++ coders was consistent. The permanent positions of OpenCV C++ jobs advertised in the UK during the past two years were over 40% of the total advertised permanent jobs in the country. This indicates that there is serious demand of OpenCV developers for permanent positions. This increasing trend in the demand for OpenCV face detection C++ engineers will continue in the marketplace, as per the predictions of many experts in the industry. There are good reasons for the same; according to another latest market prediction, the face recognition market will cross $7.76 billion marks by 2022. Billions of dollars’ of OpenCV face recognition C++ biometric-enabled devices have been shipped recently across the globe.

This growth will continuously increase the demand for OpenCV face detection C++ engineers in the marketplace not only in North America, Europe and the Asia Pacific but also in the South Americas and African countries. This growth is anticipated as a global phenomenon for a few coming years. Nowadays it is important to hire OpenCV C++ face detection developer cause of very high demand.

Top 5 Popular Projects Based on C++ & OpenCV

There are many projects that are used for different applications in the domain of two dimensions (2D), three dimensions (3D) image sensing what you can launch after you hire OpenCV face detection C++ coder. Many of those applications have been used in commercial projects and many are still in beta releases. Among such projects based on OpenCV and C++ platforms developed by the face recognition with OpenCV developers are described below:

3D(ollar) Scanner Project

This is an interesting 3D scanner project that is able to scan all objects for the 3D printing. There are numerous features of this project as listed below:

  • It uses powerful hardware design, processing programs and Arduino sketches effectively
  • It is able to solve the point-cloud of any arbitrary position a vertical camera
  • It needs only laser line angle between vertical and incident origins
  • Easy to calibrate the camera for lens aberration

Multiple Facial Recognition Project

This is a very good example of an OpenCV based project, which is designed to identify multiple people in a huge crowd with the help of artificial intelligence-based codes with the OpenCV libraries. The main features of this project include:

  • Able to recognize multiple numbers (N) faces in a crowd
  • Uses the suitable midpoints with the help of servos to camera auto center
  • Continuous frames taken by OpenCV are fast processed via eclipse center and eclipses drawn points
  • For multiple faces more than 3 numbers, it uses the total eclipse center’s centroid point
  • The Bresenham line algorithm in the generalized form is used for the servos’ two axis movement

Color Tracking Computer Vision Project

This project focuses on the tracking of the objects based on the colors. It is a good project for video analysis and other applications. The main features of this project are given below:

  • Able to track multiple colors of an object
  • Ability to compare and analyze the modification of the colors
  • Uses OpenCV, Computer vision and hardware components simultaneously to achieve the desired objectives
  • Able to detect motions based on the colors of the objects
  • Able to differentiate objects from human
  • Able to capture the videos and then convert colors-paces
  • Very easy to scale up the features and capabilities

Pool Playing Robot Project

It is project in which a robot is constructed to play in a pool of the players for the cue ball games to challenge the human players effectively. The main features of this project are listed below:

  • The robot in this project uses logics, casualty pool playing and learned behaviors for pool playing
  • It plays an eight ball pool game against any human opponent
  • The robot is an autonomous player based on the AI algorithms and processing power
  • It is a reusable project to be used for other purposes too
  • Evaluation algorithm is the main controlling mechanism of this project

Face Recognition Home Automation System

This is an effective home automation system based on the OpenCV library. It has many great features as listed below:

  • Based on the powerful facial recognition algorithm with many accurate reading capabilities
  • It is powered by a powerful facial recognition application that runs on the desktop machine, but it will be made compliant to operate under other devices too
  • Entire information provided to the system will be kept for a long time
  • It is also powered by a high power processing on the backend

OpenCV C++ Face Detection Developer’s Resume

OpenCV is a huge library with over 5 million functions that run on different platforms, such as C++, Python, Java, Ruby on Rail, and others. You can hire OpenCV C++ face detection programmer to use his skills to increase your income. So, a good resume of an OpenCV C++ face detection developer should include the following skills, qualifications, and experience.

Scope of OpenCV C++ Developers

If we look at the startup marketplace in the USA, the demand of C++ developers with OpenCV expertise is still high with many companies offering company shares too and to hire OpenCV face detection C++ engineer. The supply of the result-oriented OpenCV C++ developers is dwindling a little bit, which is putting upward pressure on the salaries in the marketplace. In the USA market, the middle career C++ and OpenCV developer will cost about $95,228 per annum. You can find here OpenCV face detection C++ programmer for hire who are really qualified and skillful through Ukrainian outstaffing or professional employer organization companies like Mobilunity OpenCV C++ Services at very reasonable costs. If you are looking for someone who will convert c++ to Java or you want to hire FPGA developers, or create an OpenCV face detection platform, we will help!

Contact us now to get the professional-grade support of highly skilled and qualified face detection OpenCV C++ developer for hire for your face recognition projects at very competitive prices!

All salaries and prices mentioned within the article are approximate NET numbers based on the research done by our in-house Recruitment Team. Please use these numbers as a guide for comparison purposes only and feel free to use the contact form to inquire on the specific cost of the talent according to your vacancy requirements and chosen model of engagement.

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