You can also use this feature to generate a blurred background with tunable blur strength. Performance mode: For the fastest performance.Quality mode: For highest segmentation quality.The Virtual Background feature runs in two modes: All these operations use the parallelism that a GPU provides, increasing the number of streams that can be processed in real time.įigure 5. This way, single or multiple users can present at the same time in real time while retaining immersion. Another example is segmenting out users and overlaying them on their computer’s live feed. For example, if two commentators are talking about a live event, you can segment both onto the live feed of the event. You can also implement multiple creative applications, like adding multiple users in the same background. You can provide any media as a background, whether image or video. The Virtual Background feature (Figure 5) essentially generates a mask to segment out the foreground, in this case, people from the stream. To enable end users to join a meeting from an environment that is neither personal nor distracting, the Maxine Video Effects SDK offers the Virtual Background feature. This mode should be applied for higher-quality lossless videos with a lower bitrate.Įnable end users to choose virtual backgrounds This mode is more suited for a higher bitrate video. 0: Preserves low gradient information while reducing artifacts.This AI-based feature is optimized for two modes: The Video Noise Removal (Figure 3) feature of the Maxine Video Effects SDK enables you to de-noise the webcam streams and preserve details, leading to better end-user experiences.įigure 4. Compression artifacts can take many forms, but one of the most common form is a blocky artifact. This variability causes situations where the encoder has fewer bits than needed to compress the frame resulting in compression artifacts. In a streaming environment, the bandwidth available to stream the compressed content is not constant. When streaming this media, the stream bandwidth per unit of time is called bitrate. Common examples of lossy compression standards would be JPEG for images and H.264 for videos. Lossy compression typically involves discarding some of the textural information in an image as well as data encoding. These types of noises are highly dependent on the type of sensor in the camera.Įncoding artifacts in video streams are a consequence of the bandwidth constraints required to transmit frames. This is especially true in the context of end-user–generated streams, if the environment is not well lit or the camera being used is of poor quality. However, the two most common sources of noise are webcam noise and encoding artifacts.Įxamples of webcam noise sources include the camera sensor type, exposure, or illumination level. The underlying causes of video noise that make or break the end-user experience are numerous. Remove webcam video noise and reduce encoding artifacts 1: Maximum image sharpness and crispness visual effect enhancement.īy default, Upscaler’s enhancement parameter is set to 0.4.0: Increases the resolution without image enhancement.You can set Upscaler’s enhancement parameter within range: You can use this feature to scale media by 1.33x, 1.5x, 2x, 3x, and 4x. This visual effect is best used on lossless compression data such as H.264. It offers holistic enhancements while preserving the content. Super Resolution (Figure 1) generates a superior quality image with higher resolution and better textures from the provided input image. Add details and improve resolutionįor poor video quality that arises from the low resolution of the image frames, the Maxine Video Effects SDK provides two state-of-the-art AI-based visual effects: Super Resolution and Upscaler. This post demonstrates how you can run these effects with standard webcam input and easily integrate them into video conference and content creation pipelines. To solve these video quality challenges, the NVIDIA Maxine Video Effects SDK offers AI-based visual features that transform noisy, low-resolution video streams into pleasant user experiences. At the same time, these streams are the most network bandwidth-intensive part of online communication, often accompanied by noise and artifacts. The crucial part of online communication is the video stream, whether it’s a simple video call or streaming content to a broad audience. Businesses, educational institutions, and public-sector agencies are experiencing a skyrocketing demand for virtual collaboration and content creation applications. Video conferencing, audio and video streaming, and telecommunications recently exploded due to pandemic-related closures and work-from-home policies.
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