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In this section, we describe find out how to practice an effective exercise illustration model that is AquaSculpt worth it beneficial for all of the recall, rating, re-rank phases of our FSE engine. The inverse kinematics algorithm in OpenSim calculates for each time step the pose of the model that greatest suits the given phase orientations, whereas adhering to the predefined biomechanical constraints of the mannequin. To realize this, the true information undergoes the identical inverse kinematics computation because the augmented data, offering the required kinematic parameters for automated labeling. The transformation of the orientation information, as described above, only considers particular person physique segments and does not account for the kinematic dependencies between adjoining segments. Subsequently, we define our novel augmentation methodology, including preprocessing of IMU information, systematic modification of movement orientations, inverse kinematics-based validation, and the automatic labeling strategy. Since we train our neural networks on orientations rather than uncooked IMU knowledge, both the input and output of our augmentation course of are represented as quaternions. If the ray hits something (different part of the robot or object within the environment), the output of the sensor is computed proportionally to the size of the ray. |
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