Stephen Curry. Cristiano Ronaldo. Tom Brady. These future hall of famers and their pro teammates all up their game using extensive video analysis. Why should it be any different for weekend warriors and aspiring rec league stars?
Startup Pixellot has a way to offer everyone the chance to get some game, whether it’s on the court, the field or the mat.
Pixellot, based near Tel Aviv, develops AI for automated video production cameras that capture sports action, providing streaming of amateur games, coaching tools and easily shared clips.
The company is among a cadre of upstarts that enlist multiple cameras and AI to autonomously capture panoramic views and track the ball and key moments in games. Copenhagen-based Veo is working on AI cameras for amateur soccer.
Founded in 2013, Pixellot — which recently raised a $30 million Series B round of financing — claims bragging rights as the largest source of automated sports video production.
The startup produces nearly 30,000 hours of sports content a month and has sold more than 2,500 cameras packing GPUs and its software worldwide.
Customers include sports leagues, clubs and coaches across the U.S., Europe, Asia and Latin America. The company’s video-coaching features are used by soccer leagues such as the English Premier league, La Liga, LigaMX and the Bundesliga.
“Pixellot is the world leader today in automatic sports production. We cater to the entire football vertical in Mexico, for example, where it’s almost a registered religion,” said Gal Oz, CTO and founder of Pixellot.
Pixellot aims to bring low-cost video production to all amateur sports. Customers include those for basketball, football, soccer, ice hockey, volleyball, handball, lacrosse, baseball and field hockey..
Coaching with AI
Pixellot’s system enables a single person to edit and broadcast a video stream of a sports event in real time. This allows for semi-professional leagues, colleges and others to produce and offer low-cost broadcasts for video streaming. Customers can use its software suite to see multiple views of video — including the center of action, presets on a specific part of the field and replays — and mix it in real time for streaming.
Coaches use it to quickly produce video clips. Key plays can be tagged for review at a later time, and the editing suite enables coaches to review each scene, frame by frame, and cut clips to share with coaches and players.
“We collect the highlights of the game based on some deep learning processes. We know how to collect the main events and to use them after the game for a highlight clip,” said Oz.
Score for AI
Pixellot’s NVIDIA GPU-powered multi-camera systems feature as many as four cameras and capture video up to 8K. They’re intended to be installed in a fixed location for use without a camera operator. The systems can be used individually or combined, if needed, to produce stitched panoramic video to cover an entire field of action.
Pixellot’s algorithms — convolutional neural networks for image recognition — enable its software to follow the game for automatic video production and to capture highlights. In soccer, for instance, it knows that kicks on the goal are just about as important to focus on as scored goals themselves.
The startup has amassed hundred of thousands of hours of sports videos to train its algorithms to catch key moments. The company trained its algorithms on NVIDIA GPUs on local workstations.
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