Multicam software manages meeting capture
Multicam showed its all-in-one systems for video switching, PTZ camera control, storage and recording, and content delivery across live streams and podcasts at InfoComm 2017.
The platforms add a slide detection module to automatically detect when a presenter or speaker should switch between PowerPoint and video content.
Two systems - Multicam E-Learning and Multicam Tracking are available to simplify the acquisition, recording and streaming of live and recorded content to Moodle, Blackboard, YouTube, Facebook and other video platforms. Both systems provide all-in-one solutions to produce lectures, online training sessions, keynotes, conferences, and other live presentations and events.
The semi-automated Multicam E-Learning allows a single user to manage video capture, camera switching, video recording, composition and streaming tasks from a central touchscreen interface. Users can identify and switch between camera angles, with automatic video insertion in alignment with camera movements.
The fully automated Multicam Tracking incorporates an Artificial Intelligence-equipped software engine that detects a speaker’s position, anticipates movements, and correlates these events with production decisions. The information collected within the system is relayed to the cameras, which select the most suitable views. Multicam Tracking’s open-platform enables connectivity and compliance with a range of PTZ cameras.
Multicam also offers Multicam Conf, which provides a fully automated video capture and broadcast system that integrates with a number of audio conference systems; and provides support for graphics.
Its built-in AI engine defines various shot angles for each microphone used in the production, and communicates with audio conferencing systems from Bosch, Taiden and Televic to provide additional information about the speaker. Through the AI engine, an automated video mixing application selects the right camera presets according to who is speaking or presenting. Its advanced video tracking algorithm leverages facial recognition, with automatic adjustment of frames as speakers move around or change posture.