def motionStitching(M1, M2, slice, funcType):
A_endPos = M1.postures[M1.frames]
B_startPos = M2.postures[1]
pos_dif = Posture.postureDifference_v2(A_endPos, B_startPos)
# project to y-axis
new_R = np.identity(4)
new_R[:-1, :-1] = uti.projection_y(pos_dif.Rmatrix[0][:-1, :-1])
pos_dif.Rmatrix[0] = new_R
newB_postures = []
for i in range(1, M2.frames + 1):
newB_postures.append(
Posture(np.array(M2.postures[i].origin),
list(M2.postures[i].Rmatrix)))
# Alignment
for posture in newB_postures:
posture.origin = A_endPos.origin + pos_dif.Rmatrix[0][:-1, :-1] @ (
posture.origin - B_startPos.origin)
posture.Rmatrix[0][:-1, :-1] = pos_dif.Rmatrix[
0][:-1, :-1] @ posture.Rmatrix[0][:-1, :-1]
posture.Rmatrix[0][:-1, 3] = posture.origin
# Motion Warping
pos_dif = Posture.postureDifference(newB_postures[0], A_endPos)
func = None
arg = None
if funcType == 0:
func = uti.linearFunc2_t
arg = 1. / slice
elif funcType == 1:
func = uti.cosFunc_t
arg = slice
for i in range(1, slice + 1):
t = func(arg, i)
b = np.zeros(3)
for j in range(3):
b[j] = t * pos_dif.origin[j]
new_origin = newB_postures[i].origin + b
new_Rmatrix = []
for R1, R2 in zip(newB_postures[i].Rmatrix, pos_dif.Rmatrix):
new_R = np.identity(4)
new_R[:-1, :-1] = uti.addByT(R1[:-1, :-1], R2[:-1, :-1], t)
# new_R[:-1,:-1] = uti.addByT(np.identity(3),R2[:-1,:-1],t)
new_Rmatrix.append(new_R)
new_Rmatrix[0][:-1, 3] = new_origin
newB_postures[i] = Posture(new_origin, new_Rmatrix)
# Concatenate
for i in range(1, M2.frames):
newB_postures[i].make_framebuffer(M1.skeleton.root)
M1.postures.append(newB_postures[i])
M1.frames = M1.frames + (M2.frames - 1)
return M1
def motionWarping(self, frame, new_posture, startF, endF, funcType):
posture_dif = Posture.postureDifference(self.postures[frame],
new_posture)
new_postures = []
for posture in self.postures:
new_postures.append(
Posture(np.array(posture.origin), list(posture.Rmatrix)))
first_slice = frame - startF
second_slice = endF - frame
first_func = None
second_func = None
firstArg = None
secondArg = None
if funcType == 0:
first_func = uti.linearFunc_t
second_func = uti.linearFunc2_t
firstArg = 1. / first_slice
secondArg = 1. / second_slice
elif funcType == 1:
first_func = uti.sinFunc_t
second_func = uti.cosFunc_t
firstArg = first_slice
secondArg = second_slice
for i in range(startF, frame + 1):
t = first_func(firstArg, i - startF)
b = np.zeros(3)
for j in range(3):
b[j] = t * posture_dif.origin[j]
new_origin = self.postures[i].origin + b
new_Rmatrix = []
for R1, R2 in zip(self.postures[i].Rmatrix, posture_dif.Rmatrix):
new_R = np.identity(4)
new_R[:-1, :-1] = uti.addByT(R1[:-1, :-1], R2[:-1, :-1], t)
new_Rmatrix.append(new_R)
new_postures[i] = Posture(new_origin, new_Rmatrix)
for i in range(frame + 1, endF + 1):
t = second_func(secondArg, i - frame)
b = np.zeros(3)
for j in range(3):
b[j] = t * posture_dif.origin[j]
new_origin = self.postures[i].origin + b
new_Rmatrix = []
for R1, R2 in zip(self.postures[i].Rmatrix, posture_dif.Rmatrix):
new_R = np.identity(4)
new_R[:-1, :-1] = uti.addByT(R1[:-1, :-1], R2[:-1, :-1], t)
new_Rmatrix.append(new_R)
new_postures[i] = Posture(new_origin, new_Rmatrix)
for posture in new_postures:
posture.Rmatrix[0][:-1, 3] = posture.origin
posture.make_framebuffer(self.skeleton.root)
return Motion(self.skeleton, new_postures, self.frames,
self.frame_rate)
