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Sports

When technology is part of the game

After more than ten years of experience developing sports video analysis software, we empower you to collect, analyze, visualize, and truly understand your sports data like never before.

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Take your video analysis solution to the next level

Use the latest technologies and state-of-the-art machine learning algorithms to extract the most valuable information from a video.

Streamline your video analysis process by automating tasks that require countless hours of manual effort. Optimize your workflow, save time, and focus on what matters most: making data-driven decisions that drive results.

Stay ahead with AI solutions

Take full advantage of our Multimedia Edge AI tools and products designed to transform your company’s video analysis and decision-making processes.

  • Computer Vision: Take powerful insights with precise video analysis, leveraging AI-powered vision technology.
  • Non-Linear Editing: Seamlessly edit and process videos with efficiency and flexibility.
  • Multi-Sport Optimization: Our solutions are tailored for multiple sports, utilizing customized models and algorithms for each discipline to extract accurate, sport-specific data and actionable insights.

From the code to the action

Developments that bring real-world results, these case studies show how our solutions help your business achieve goals and enhance user experiences.

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A client in the sports technology sector, operating across football, rugby, and hockey, required a real-time sports video analysis solution capable of running multiple AI models in parallel for tasks such as object detection, player tracking, and camera calibration. The system needed to deliver high-performance processing and improved accuracy while maintaining low latency.

Proposed solutions

Practical solutions for real-world results

Field-ready AI solution with real-time sports insights

A complete sports video analysis application was developed, integrating multiple AI models and functionalities across various domains, including object detection, multi-object tracking, and camera calibration*. Model accuracy was improved through synthetic data generation, enabling robust performance in a wide range of sports scenarios.

The system featured a hardware-accelerated graphics environment tailored to the customer’s requirements, along with a custom, high-performance video player capable of reproducing synthetic video streams. All AI models were optimized for real-time execution on edge devices, providing a responsive and field-ready sports technology solution.

Our achievements

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industry
outcome

OUTCOME

Real-time, high-accuracy sports analysis on edge devices

Testimonial image for Founder & LongoMatch

For years, Fluendo has been a key strategic partner for LongoMatch, providing the robust multimedia backend our video analysis software relies on. Their deep expertise in GStreamer is the stable foundation upon which our product is built.

We recently extended our collaboration to develop a cutting-edge, AI-based video analysis SDK. Fluendo’s technical skill and experience in edge AI and vision AI were instrumental in turning our ideas into a successful project. This new technology will empower us to deliver powerful, next-generation video analysis features to our users.

Fluendo isn’t just a supplier; they are a partner that helps us build the future of sports video analysis.

Founder

LongoMatch

Bits & Bytes

Explore our blog, one byte at a time. Our team unpack our latest news, industry insights and in-depth articles to connect you with the multimedia world.

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Read more about our work

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NMS-Raster: Post-processing bounding boxes using the “G” in GPU
sports, multimedia-edge-ai, gstreamer, fluendo-ai-plugins, raven

NMS-Raster: Post-processing bounding boxes using the “G” in GPU

Table of contents NMS-Raster: Post-processing bounding boxes using the “G” in GPU The bounding box problem Classical NMS NMS-Raster: Z-Aware rasterized suppression Advantages of the approach Implementation Instanced drawing into integer framebuffer Contribution histogram Threshold filtering Strengths of the design Performance NMS-Raster: Post-processing bounding boxes using the “G” in GPU In this article, we explore the challenges of bounding box post-processing in AI-powered object detection and demonstrate how our high-performance inference engine, Raven, addresses them from a novel angle.

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AI-based soccer metrics extraction app
sports, multimedia-edge-ai, gstreamer, outsource, raven

AI-based soccer metrics extraction app

AI-powered soccer app that extracts tactical metrics like player distances, movement tracks, and team identification from broadcast video—all in real time and without manual intervention.

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Image superresolution with GStreamer
broadcasting, video-surveillance, sports, multimedia-edge-ai, gstreamer, events, fluendo-ai-plugins, raven

Image superresolution with GStreamer

Our custom AI plugin leverages advanced GAN-based models to upscale images with remarkable detail and clarity. It transforms low-res inputs into high-res outputs for medical imaging, satellite imagery, or entertainment, delivering flexibility, precision, and speed. Discover more in this article!

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Real-time AI Background Removal with GStreamer
broadcasting, video-surveillance, sports, education, multimedia-edge-ai, gstreamer, events, fluendo-ai-plugins, raven

Real-time AI Background Removal with GStreamer

Imagine achieving professional, distraction-free backgrounds in real-time, no green screen required. That's what our Background Removal plugins do!

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