From Video to Action: PowerTech Breaks Through Single-View 3D Reconstruction Accuracy, Turning Human Experience into Robot Training Data

PowerTech has developed a method to convert single-view RGB videos into high-precision 3D action data for robotic training. The approach involves high-accuracy 3D hand pose reconstruction, autonomous truth systems for validation, and automated pipelines for large-scale processing. This enables the transformation of human demonstrations into structured data that can be used to train robots, with applications in imitation learning and embodied perception. The system achieves sub-millimeter accuracy in hand pose reconstruction and supports real-time mapping to robotic arms and dexterous hands.