def _solve_sbl_multicore_impl(self, index):
"""
Implementation of Lambertian Photometric stereo based on sparse regression (Sparse Bayesian learning)
Satoshi Ikehata, David P. Wipf, Yasuyuki Matsushita, Kiyoharu Aizawa:
Robust photometric stereo using sparse regression. CVPR 2012: 318-325
:param index: an index of a measurement (row of M)
:return: a row vector of surface normal at pixel index specified by "index"
"""
A = self.L.T
b = np.array([self.M[index, :]]).T
n = rpsnumerics.sparse_bayesian_learning(
A, b) # row vector of a surface normal at pixel "index"
return n.ravel()
def _solve_sbl(self):
"""
Lambertian Photometric stereo based on sparse regression (Sparse Bayesian learning)
Satoshi Ikehata, David P. Wipf, Yasuyuki Matsushita, Kiyoharu Aizawa:
Robust photometric stereo using sparse regression. CVPR 2012: 318-325
:return: None
Compute surface normal : numpy array of surface normal (p \times 3)
"""
A = self.L.T
self.N = np.zeros((self.M.shape[0], 3))
if self.foreground_ind is None:
indices = range(self.M.shape[0])
else:
indices = self.foreground_ind
for index in indices:
b = np.array([self.M[index, :]]).T
n = rpsnumerics.sparse_bayesian_learning(A, b)
self.N[index, :] = n.ravel()
self.N = normalize(self.N, axis=1)