. Many patients tape particularly unstable joints (like shoulders or knees) with kinesiology tape or athletic tape as taught by their therapist.Avoiding sudden, jarring movementsandhigh-impact activitiesis important. Activities like running and jumping put a lot of force on the joints and can l...
The segmentation models are trained on\(112\times 144\times 64\)patches form resulted VOIs, which differ slightly on all scans. Adam optimizer is used with initial learning rate of 0.0001. Each model is trained for 100 epochs (8000 iterations) to ensure convergence. We did not perform specifi...
3D Human Pose Estimation (3D-HPE) is a highly active and evolving research area in computer vision with numerous applications such as extended reality, act
The steps for evaluating human action similarity based on the action information encoder are as follows: (1) Use a sliding window of size w and stride r to divide point sequence patches, X1 and X2, respectively: Pi1 ,j1 ,k1 and Pi2 ,j2 ,k2 into two sets of skeletal key X1 = {...
A survey on deep 3D human pose estimation 3 Single-person 3D-HPE methods Page 15 of 53 24 This section provides an overview of current techniques in single-person 3D-HPE, focusing on predicting the 3D coordinates of key body joints, including the head, shoulders, elbows, and knees....
In particular, DeepMoCap deals with single-person, marker-based motion capture using a set of retro-reflective straps and patches (reflector-set: a set of retro-reflective straps and patches, called reflectors for the sake of simplicity) from off-the-shelf materials (retro-reflective tape) and...
In particular, DeepMoCap deals with single-person, marker-based motion capture using a set of retro-reflective straps and patches (reflector-set: a set of retro-reflective straps and patches, called reflectors for the sake of simplicity) from off-the-shelf materials (retro-reflective tape) and...
To overcome these limitations, several attempts have been made recently to use DNNs. DNNs with a large number of layers can learn progressively complex features effectively from input images. Furthermore, a DNN learns to detect complex patterns for a whole image, not just local patches. The Deep...
In other words, multiple sensor devices are required for HAR. Sensors 2022, 22, 8642 10 of 17 Ground-Truth Class Standing Sitting Lying down Walking Climbing stairs Waist bends forward Frontal elevation of arms Knees bending Cycling Jogging Running Jump front and back We also investigate the ...