GStreamer is a versatile, pipeline-based multimedia framework that seamlessly connects various media processing tools, enabling efficient, complex multimedia workflows across platforms.
GStreamer is a powerful, open-source multimedia framework packed with features. It is mainly used to develop media applications for streaming, playback, non-linear editing, and more. Designed to simplify building applications that handle audio, video, and synchronized metadata, GStreamer leverages a flexible plugin system, providing various codecs and media processing tools.
Compatible with all major operating systems— including Linux, Android, Windows, macOS, and iOS —GStreamer also supports diverse hardware architectures such as x86, ARM, MIPS, and SPARC. It offers an extensive library of multimedia plugins (encoders, decoders, filters, etc.) and allows easy integration of third-party plugins. With comprehensive, developer-friendly documentation and a robust community contributing to its continuous development, GStreamer is a top choice for creating complex, efficient multimedia workflows.
GStreamer is a powerful, open-source multimedia framework packed with features. It is mainly used to develop media applications for streaming, playback, non-linear editing, and more. Designed to simplify building applications that handle audio, video, and synchronized metadata, GStreamer leverages a flexible plugin system, providing various codecs and media processing tools.
Compatible with all major operating systems— including Linux, Android, Windows, macOS, and iOS —GStreamer also supports diverse hardware architectures such as x86, ARM, MIPS, and SPARC. It offers an extensive library of multimedia plugins (encoders, decoders, filters, etc.) and allows easy integration of third-party plugins. With comprehensive, developer-friendly documentation and a robust community contributing to its continuous development, GStreamer is a top choice for creating complex, efficient multimedia workflows.
Working with multimedia is challenging. Therefore, selecting the correct framework to process audio and video streams is crucial to ensuring a successful project. In Fluendo, we believe that developers should consider the following:
GStreamer stands out in each of these areas. Its intelligent plugin architecture and robust core library simplify application development, offering reliable, well-tested components to meet diverse multimedia needs.
Working with multimedia is challenging. Therefore, selecting the correct framework to process audio and video streams is crucial to ensuring a successful project. In Fluendo, we believe that developers should consider the following:
GStreamer stands out in each of these areas. Its intelligent plugin architecture and robust core library simplify application development, offering reliable, well-tested components to meet diverse multimedia needs.
Fluendo offers a complete suite of GStreamer-based audio and video plugins, each equipped with patent licensing for commercial use. These plugins are compatible with any operating system (Windows, macOS, Linux, Android, and iOS) and can also integrate with other multimedia frameworks, such as FFmpeg, through our developed Enablers.
Designed for multimedia developers, the Fluendo SDK provides an intuitive API that enables seamless, GStreamer-powered media playback on applications across supported operating systems (Windows, Linux, macOS, Android, and iOS) and architectures, including x86, x86_64, and ARM.
We put our expertise and support at your disposal to optimize or port plugins across hardware platforms or to develop new plugins and features tailored to your project’s needs. With our consulting services, we can help your business grow.
Fluendo offers a complete suite of GStreamer-based audio and video plugins, each equipped with patent licensing for commercial use. These plugins are compatible with any operating system (Windows, macOS, Linux, Android, and iOS) and can also integrate with other multimedia frameworks, such as FFmpeg, through our developed Enablers.
Designed for multimedia developers, the Fluendo SDK provides an intuitive API that enables seamless, GStreamer-powered media playback on applications across supported operating systems (Windows, Linux, macOS, Android, and iOS) and architectures, including x86, x86_64, and ARM.
We put our expertise and support at your disposal to optimize or port plugins across hardware platforms or to develop new plugins and features tailored to your project’s needs. With our consulting services, we can help your business grow.
The company delivers advanced technology solutions that enhance public safety and border security, protecting critical infrastructure for nations worldwide, including multiple NATO members. To support these mission-critical requirements, Fluendo developed a highly modular video streaming and recording platform based on GStreamer, designed as a …
The company is an innovative leader in XR (Extended Reality) solutions, delivering immersive telepresence experiences through advanced wearable technologies for the industrial, education, and entertainment sectors. To enhance performance on next-generation XR devices, the company partnered with Fluendo to optimize GStreamer multimedia pipelines for …
The company develops autonomous marine vehicles for long-duration missions in remote and harsh environments, supporting environmental monitoring, inspection, and research applications. These platforms require reliable, real-time video communication even under limited or unstable bandwidth conditions. To address these challenges, the company …
The company develops a modern AI-powered camera system designed to create safer workplaces and enable smarter business operations across industries. To strengthen its multimedia engineering capabilities, the company partnered with Fluendo to enhance its team’s expertise in GStreamer with a strong focus on Rust-based development. Recognizing Rust’s …
In high-risk environments such as elderly care facilities, hospitals, public transit stations, or workplace safety zones, detecting human falls instantly is essential for preventing serious injuries and enabling rapid emergency response. However, continuous manual video surveillance monitoring is resource-intensive and prone to oversight. A growing …
Public spaces such as transportation hubs, university campuses, shopping centres, and event venues face growing security risks from both concealed and openly carried knives. These threats put heavy pressure on security teams to detect weapons quickly and respond before incidents escalate. Traditional manual monitoring of multiple CCTV or IP camera …
In modern live broadcasting and video surveillance, operators struggle to keep moving subjects framed when using traditional PTZ (Pan-Tilt-Zoom) cameras in dynamic environments such as lecture halls, theaters, or public spaces. An AI-driven subject tracking solution can autonomously detect and follow speakers, performers, or persons of interest, …
Did you miss Fluendo's talks at the GStreamer Conference? Don't worry! Recordings are available in this blog post.
In fast-paced law enforcement operations, every second counts. Officers rely on live camera feeds from traffic intersections, security checkpoints, and other monitored locations to respond to unfolding events with precision and accuracy. While AI-powered media analytics platforms like Intelion can extract critical insights—such as detecting faces, license plates, objects, and more—there are moments when human eyes need to see events unfold in real time. Fluendo’s Recasting and Recording System (RRS) bridges this gap, delivering low-latency live streams alongside AI-generated insights.
This post details a hands-on consulting engagement to resolve video playback issues in a React Native mobile app using GStreamer, with practical insights for developers facing similar challenges.
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.