我正在将一个矩阵(M)转换为四元数,以便我可以在两个不同的变换矩阵之间进行线性插值,从而使图像平滑动画化,其中我需要自己制作视频帧。当我将四元数转换回矩阵进行测试时,这个新矩阵与成为四元数的那个矩阵非常不同。
import numpy as np
from transforms3d import quaternions
M = np.array([[ 0.757403109, -0.186744161, 145.541734],
[ -0.154492906, 0.626185286, 100.878814],
[ -0.000294826495, -0.000344726091, 1.00000000]])
quat = quaternions.mat2quat(M)
testM = quaternions.quat2mat(quat)
print("TEST: M original")
print(M)
print("TEST: quat back to mat (testM)")
print(testM)
print("Why not the same")
print ("quat")
print(quat)
print("quat of testM")
print(quaternions.mat2quat(testM))
#Scaling gives same result, scale M to be -1. to 1
mmax = np.amax(M)
scaleTestM = M / mmax
print("M Scaled")
print(scaleTestM)
quatOfScaled = quaternions.mat2quat(scaleTestM)
print("Quat of scaled")
print(quaternions.quat2mat(quatOfScaled))
我是否漏掉了四元数实际上可以表示的某些内容,或者代码有误?如果这种方法行不通,欢迎提出其他关于如何在两个转换矩阵之间平稳移动的建议。
Python 3.6
控制台输出如下:
TEST: M original
[[ 7.57403109e-01 -1.86744161e-01 1.45541734e+02]
[ -1.54492906e-01 6.26185286e-01 1.00878814e+02]
[ -2.94826495e-04 -3.44726091e-04 1.00000000e+00]]
TEST: quat back to mat (testM)
[[ 0.38627453 -0.42005089 0.8211877 ]
[-0.54462197 0.61466344 0.57059247]
[-0.74443193 -0.6676422 0.00865989]]
Why not the same
quat
[ 0.70880143 -0.43673539 0.55220671 -0.04393723]
quat of testM
[ 0.70880143 -0.43673539 0.55220671 -0.04393723]
M Scaled
[[ 5.20402697e-03 -1.28309699e-03 1.00000000e+00]
[ -1.06150244e-03 4.30244486e-03 6.93126372e-01]
[ -2.02571789e-06 -2.36857210e-06 6.87088145e-03]]
Quat of scaled
[[ 0.38627453 -0.42005089 0.8211877 ]
[-0.54462197 0.61466344 0.57059247]
[-0.74443193 -0.6676422 0.00865989]]