def calc_geodesic_matrix(bones, mesh_v, surface_geodesic, mesh_filename, subsampling=False):
"""
calculate volumetric geodesic distance from vertices to each bones
:param bones: B*6 numpy array where each row stores the starting and ending joint position of a bone
:param mesh_v: V*3 mesh vertices
:param surface_geodesic: geodesic distance matrix of all vertices
:param mesh_filename: mesh filename
:return: an approaximate volumetric geodesic distance matrix V*B, were (v,b) is the distance from vertex v to bone b
"""
if subsampling:
mesh0 = o3d.io.read_triangle_mesh(mesh_filename)
mesh0 = mesh0.simplify_quadric_decimation(3000)
o3d.io.write_triangle_mesh(mesh_filename.replace(".obj", "_simplified.obj"), mesh0)
mesh_trimesh = trimesh.load(mesh_filename.replace(".obj", "_simplified.obj"))
subsamples_ids = np.random.choice(len(mesh_v), np.min((len(mesh_v), 1500)), replace=False)
subsamples = mesh_v[subsamples_ids, :]
surface_geodesic = surface_geodesic[subsamples_ids, :][:, subsamples_ids]
else:
mesh_trimesh = trimesh.load(mesh_filename)
subsamples = mesh_v
origins, ends, pts_bone_dist = pts2line(subsamples, bones)
pts_bone_visibility = calc_pts2bone_visible_mat(mesh_trimesh, origins, ends)
pts_bone_visibility = pts_bone_visibility.reshape(len(bones), len(subsamples)).transpose()
pts_bone_dist = pts_bone_dist.reshape(len(bones), len(subsamples)).transpose()
# remove visible points which are too far
for b in range(pts_bone_visibility.shape[1]):
visible_pts = np.argwhere(pts_bone_visibility[:, b] == 1).squeeze(1)
if len(visible_pts) == 0:
continue
threshold_b = np.percentile(pts_bone_dist[visible_pts, b], 15)
pts_bone_visibility[pts_bone_dist[:, b] > 1.3 * threshold_b, b] = False
visible_matrix = np.zeros(pts_bone_visibility.shape)
visible_matrix[np.where(pts_bone_visibility == 1)] = pts_bone_dist[np.where(pts_bone_visibility == 1)]
for c in range(visible_matrix.shape[1]):
unvisible_pts = np.argwhere(pts_bone_visibility[:, c] == 0).squeeze(1)
visible_pts = np.argwhere(pts_bone_visibility[:, c] == 1).squeeze(1)
if len(visible_pts) == 0:
visible_matrix[:, c] = pts_bone_dist[:, c]
continue
for r in unvisible_pts:
dist1 = np.min(surface_geodesic[r, visible_pts])
nn_visible = visible_pts[np.argmin(surface_geodesic[r, visible_pts])]
if np.isinf(dist1):
visible_matrix[r, c] = 8.0 + pts_bone_dist[r, c]
else:
visible_matrix[r, c] = dist1 + visible_matrix[nn_visible, c]
if subsampling:
nn_dist = np.sum((mesh_v[:, np.newaxis, :] - subsamples[np.newaxis, ...])**2, axis=2)
nn_ind = np.argmin(nn_dist, axis=1)
visible_matrix = visible_matrix[nn_ind, :]
os.remove(mesh_filename.replace(".obj", "_simplified.obj"))
return visible_matrix
def calc_geodesic_matrix(bones, mesh_v, surface_geodesic, mesh_filename):
"""
calculate volumetric geodesic distance from vertices to each bones
:param bones: B*6 numpy array where each row stores the starting and ending joint position of a bone
:param mesh_v: V*3 mesh vertices
:param surface_geodesic: geodesic distance matrix of all vertices
:param mesh_filename: mesh filename
:return: an approaximate volumetric geodesic distance matrix V*B, were (v,b) is the distance from vertex v to bone b
"""
mesh_trimesh = trimesh.load(mesh_filename)
origins, ends, pts_bone_dist = pts2line(mesh_v, bones)
pts_bone_visibility = calc_pts2bone_visible_mat(mesh_trimesh, origins,
ends)
pts_bone_visibility = pts_bone_visibility.reshape(len(bones),
len(mesh_v)).transpose()
pts_bone_dist = pts_bone_dist.reshape(len(bones), len(mesh_v)).transpose()
# remove visible points which are too far
for b in range(pts_bone_visibility.shape[1]):
visible_pts = np.argwhere(pts_bone_visibility[:, b] == 1).squeeze(1)
if len(visible_pts) == 0:
continue
threshold_b = np.percentile(pts_bone_dist[visible_pts, b], 15)
pts_bone_visibility[pts_bone_dist[:, b] > 1.3 * threshold_b, b] = False
visible_matrix = np.zeros(pts_bone_visibility.shape)
visible_matrix[np.where(
pts_bone_visibility == 1)] = pts_bone_dist[np.where(
pts_bone_visibility == 1)]
for c in range(visible_matrix.shape[1]):
unvisible_pts = np.argwhere(pts_bone_visibility[:, c] == 0).squeeze(1)
visible_pts = np.argwhere(pts_bone_visibility[:, c] == 1).squeeze(1)
if len(visible_pts) == 0:
visible_matrix[:, c] = pts_bone_dist[:, c]
continue
for r in unvisible_pts:
dist1 = np.min(surface_geodesic[r, visible_pts])
nn_visible = visible_pts[np.argmin(surface_geodesic[r,
visible_pts])]
if np.isinf(dist1):
visible_matrix[r, c] = 8.0 + pts_bone_dist[r, c]
else:
visible_matrix[r, c] = dist1 + visible_matrix[nn_visible, c]
return visible_matrix