Non-assisted scene calibration: an innovative impact on sports analysis
In this post, we explore the transition from traditional manual sports video analysis to cutting-edge autonomous scene calibration.
Enhance your multimedia processing GStreamer pipelines with our AI hardware-accelerated GStreamer plugins. Powered by our Raven AI Engine, Fluendo AI Plugins offer custom solutions to enhance different video and audio applications. We offer cross-platform and production-ready solutions optimized for Edge AI that can be used across a wide range of devices and platforms, from desktop PC’s to embedded systems.
Easily integrate advanced AI features into existing GStreamer workflows without requiring extensive reconfiguration or disrupting established processes, enabling users to enhance their multimedia content effortlessly.
Run AI solutions efficiently on-device, reducing latency and maximizing resource usage for applications requiring real-time performance in resource-constrained environments like IoT and autonomous systems or offline processing in multimedia applications.
Deploy AI solutions across different hardware environments without worrying about your GPU/CPU/NPU configurations. Our plugins ensure orthogonal and optimal runtime performance in multiple adapters (NVIDIA, AMD, Intel, …)
Each plugin comes pre-configured to handle AI tasks, requiring no AI expertise. Built on Fluendo’s proprietary Raven AI Engine, the plugins offer seamless integration with GStreamer. Our system stands out by delivering high-performance solutions that work efficiently even on low-power edge devices.
Fluendo AI Plugins empower businesses to transform their video content workflows by improving processing speed, accuracy, and quality across a range of applications.
This plugin enables real-time background subtraction from webcam feeds, seamlessly integrating the resulting video into desktop presentations or virtual environments. It is ideal for video conferencing, live streaming, and content creation.
This plugin employs a Generative Adversarial Network (GAN) to upscale video and image resolutions by 4x, enhancing the quality of low-resolution content. This is crucial for media restoration, video streaming, and any application where image clarity is paramount.
Stay updated with news, our latest projects, insights, articles, and open-source contributions from the Fluendo team.
In this post, we explore the transition from traditional manual sports video analysis to cutting-edge autonomous scene calibration.
Explore in this entry how sports analysis has evolved with computer vision, from manual scrutiny to AI integration.
Dive into this article, where we showcase significant improvements in detection accuracy and tracking performance, and learn about our ongoing commitment to innovation in multimedia edge AI.
Discover how Fluendo's Innovation Days have unleashed the power of post-training optimization for AI at the edge in this blog.