Search Results for "physical"

...Utilizing lightweight model architectures together with GPU acceleration throughout the pipeline, the solution delivers real-time performance-critical for live experiences. Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control. For example, it can form the basis for yoga, dance, and fitness applications. It can also enable the overlay of digital content and information on top of the physical world in augmented reality.

...By implementing NDI input sources, dedicated output transports, and special filter modes, it allows creativity-oriented workflows such as capturing remote cameras, sharing scenes between machines, or distributing live feeds without capture cards or physical cabling. The plugin works with the NDI runtime and supports modern versions of OBS Studio across Windows, macOS, and Linux, enabling streamers and production setups to leverage low-latency, high-quality media over local networks for multi-device collaboration or extended setups. DistroAV’s development community focuses on maintaining compatibility with the latest OBS releases and NDI v6 tooling while addressing bugs and extending feature requests.

IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch Mozaic Many Outputs Physical Inputs Streaming Protocols File Formats Presets Vods/Series server-side support Pay per view channels Channels on demand HTTP Live Streaming (HLS) server-side support Public API, client server communication via JSON RPC Protocol gzip compression Deep learning video analysis Supported deep learning frameworks: Tensorflow NCSDK Caffe ML Hardware:

reacTIVision is a computer vision framework for the fast and robust tracking of markers attached on physical objects, and the creation of multi-touch surfaces. It was designed for the rapid development of table-based tangible user interfaces.