Monthly Archives: September 2018

OPT Pose Recognition

As part of the V2 Gnocchi update, OpenPTrack now uses machine learning for pose recognition alongside person tracking and its new object tracking capabilities. OPT pose recognition extends the OpenPose skeletal tracking library to multiple cameras, and includes the ability to train the system to detect unique poses. Early adopters include UCLA and Indiana University STEP researchers, […]

Real-time Movement Analysis – OpenMoves

OpenPTrack senses where people are, but not how they move. That’s where OpenMoves comes in. Interpreting human motion data in real time is an important capability for mixed reality applications.  Being developed by UCLA REMAP, OpenMoves is a new toolset for generating higher-level short-time features, as well as learning and recognizing […]