A Copenhagen startup developed a deep learning-based camera system that can detect where the action is on the soccer field, and automatically zoom and follow the ball – just like how a camera operator would do.
“Today, less than 1 percent of all football matches are recorded,” says Veo co-founder and CEO Henrik Teisbæk. “This is because in order to record a football match properly, you need a cameraman to be filming from an elevated position for 90 minutes, and then be able to edit the footage afterwards. Most teams simply don’t have the resources required for this, meaning that millions of goals and unique footballing moments are never viewed or shared by the players”.
Using CUDA, TITAN X GPUs and the cuDNN-accelerated TensorFlow deep learning framework, the small startup trained their deep neural networks on over one million soccer-related images to automatically track the ball and players with consistency and precision.
“We have spent nearly two years developing the technology to detect where on the pitch a camera operator would point and zoom,” Teisbæk explains.
Combined with Veo’s camera mount consisting of two 4K cameras that produce a full 180-degree panoramic view of the entire filed, their trained AI technology takes advantage of compute resources in the cloud to follow the action.
Read more >
AI Technology Automatically Records Soccer Matches

Aug 31, 2017
Discuss (0)
AI-Generated Summary
- A Copenhagen startup, Veo, has created a camera system that uses deep learning to automatically track and zoom in on the action on a soccer field.
- The system was developed using CUDA, TITAN X GPUs, and the cuDNN-accelerated TensorFlow deep learning framework, and was trained on over one million soccer-related images.
- Veo's technology aims to make it possible for more soccer matches to be recorded, as currently less than 1 percent of matches are recorded due to the need for a cameraman and editing resources.
AI-generated content may summarize information incompletely. Verify important information. Learn more