1. Linear Combinations of Single Arm Motion
Eight markers are attached to the right arm for tracking by a commercial motion capture system (a six infrared-camera-system,
Motion Analysis Corporation).
Once the ground truth of 3-D position of each markers was captured, we started learning the motion model by PCA: Sampling from original data, with the overlapped offset of 5 frames, we got 629 10-frame segments, each represented by 240 numbers (8 markers times 3 dimensions times 10 frames). After subtracting a mean vector we did SVD: X=USV', then columns of U are the basis functions (eigenvectors), diagonal elements of S are singluar values. The principal eigenvectors will be useful to synthesize a movement or analysis the true movement in the video. Below is a synthesis demo of right arm motion:
= MeanV0 + Sum_i(Ci*EigenVi) =
+C1*
+C2*
+C3*
+...
2. Linear Combinations of Upper Body Motion
Thirteen markers are attached to the upper human body (3 on the head, 4 for each arm, 2 on the torso) for tracking by a commercial motion capture system (a six infrared-camera-system,
Motion Analysis Corporation).
Once the ground truth of 3-D position of each markers was captured, we started learning the motion model by PCA: Sampling from original data, with the overlapped offset of 5 frames, we got 629 10-frame segments, each represented by 390 numbers (13 markers times 3 dimensions times 10 frames). After subtracting a mean vector we did SVD: X=USV', then columns of U are the basis functions (eigenvectors), diagonal elements of S are singluar values. The principal eigenvectors will be useful to synthesize a movement or analysis the true movement in the video. Below is a synthesis demo of upper body motion:
= MeanV0 + Sum_i(C'i*EigenVi) =
+C'1*
+C'2*
+C'3*
+C'4*
+...