  This paper introduces a new set of video analytics plugins developed for the
FFmpeg framework. Multimedia applications that increasingly utilize the FFmpeg
media features for its comprehensive media encoding, decoding, muxing, and
demuxing capabilities can now additionally analyze the video content based on
AI models. The plugins are thread optimized for best performance overcoming
certain FFmpeg threading limitations. The plugins utilize the Intel OpenVINO
Toolkit inference engine as the backend. The analytics workloads are
accelerated on different platforms such as CPU, GPU, FPGA or specialized
analytics accelerators. With our reference implementation, the feature of
OpenVINO as inference backend has been pushed into FFmpeg mainstream
repository. We plan to submit more patches later.

Multimedia;Artificial Intelligence