NKFI II.

NKFIA_infoblokk_kerettel_projekt_fekv...

Objects tracking using artificial intelligence, computer vision and synthetic data.

Beneficiary Name: TEQBALL Ltd.

Project title: "Objects tracking using artificial intelligence, computer vision and synthetic data”

The amount of the support: HUF 243,316,920

Level of support: 58,113915%

Presentation of the Project content:


These days one of the most important issues are that the communities, those who are spending most of their time in front of the screen (maybe they need to because of their work or even youngsters) they do not exercise enough, therefore the level of obesity is high and keep growing in the European Union and in other parts of the world as well. This is a problem in Hungary that the time what people had spent in front of screens (TV, computer) are extremely high. Then there is the multi-screen effect, which means that youngsters sitting in front of more than one screen. However, if we want to reach a big crowd and make them to spend more time with sports, this is not necessary to introduce exercise without computers in the world of the smart phones.


Our Company think such experimental development which use the available smartphones to introduce different ball games into everyday life, activated at home. How the youngsters playing together in PlayStation or other kind of game consoles, now with using smartphones, in virtual reality, even ball games, skill games but in games which requires movement they can play together in real time with computer vision and analysation of the picture, thereby they can develop their skills in ball games in a playful way.
As a result of our development they are capable to exercise at home both in natural or in artificial light and they can find new communities or find new friends in national or even in international level.


The main goal of our project is to achieve serious results in the World and in Hungary in the most popular ball games like football. Our results are measurable because we will have data about the user’s activity. The application will be available for other developers as well because it will connect to the open source system only if its commercially reasonable for the company. Hereby the technological development can reach bigger publicity.


What is new in this project is how we can teach the computer vision and the artificial intelligence with synthetic materials, which built in algorithms can cause a more effective learning process than the rivals. Normally the ball recognizer systems are not existing with artificial intelligence or which exist was made to broadcast or Tv broadcasting, but these systems are not to meet needs of the crowd.


By the end of the project the experimental development may results in a method that, at the end of the research period, will create a framework. This can even lead to applications development for commercial purposes. Thanks to that we are planning to connect to open source systems (Yolo open source system) our process can be licensed for educational or commercial use.

Our research background is based on our well-qualified specialist staff. The head of research is Viktor Huszár - a student of the Doctoral School of Military Engineering at the National University of Public Service. The topic of the research includes the so-called block chain, computer vision and Artificial Intelligence. In connection with these, several appearances - as robot warfare, communication - have taken place and several lectures have already been given in the subject. Economist, László Bárdy - who is the project's operations manager - has worked on developments that have reached millions of people globally, in turbulent markets with flight-related reservation system.

Our focus area centres on ball sports especially football, which is the most popular sport in the world. There are more than 3 billion football players, who are hobby footballers. In addition, based on Teqball's existing success, we currently have over 1.2 million communities of our own.

Planned completion date of the Project: 31.12.2021.

Project identification number: 2019-1.1.1-PIACI-KFI-2019-00290