Suppose I have colmap camera poses, is it possible and how to obtain a new view of input image I (planar object) from a different viewpoint/camera pose using those poses?
Colmap camera poses has following data:
extr = cam_extrinsics[key]
intr = cam_intrinsics[extr.camera_id]
height = intr.height
width = intr.width
uid = intr.id
R = np.array(qvec2rotmat(extr.qvec))
T = np.array(extr.tvec)
if intr.model=="SIMPLE_PINHOLE":
focal_length_x = intr.params[0]
FovY = focal2fov(focal_length_x, height)
FovX = focal2fov(focal_length_x, width)
fx = fy = intr.params[0]
cx = intr.params[1]
cy = intr.params[2]
elif intr.model=="PINHOLE":
focal_length_x = intr.params[0]
focal_length_y = intr.params[1]
FovY = focal2fov(focal_length_y, height)
FovX = focal2fov(focal_length_x, width)
fx = intr.params[0]
fy = intr.params[1]
cx = intr.params[2]
cy = intr.params[3]
class DummyCamera:
def __init__(self, uid, R, T, FoVx, FoVy, K, image_width, image_height):
self.uid = uid
self.R = R
self.T = T
self.FoVx = FoVx
self.FoVy = FoVy
self.K = K
self.image_width = image_width
self.image_height = image_height
self.projection_matrix = getProjectionMatrix(znear=0.01, zfar=100.0, fovX=FoVx, fovY=FoVy).transpose(0,1).cuda()
self.world_view_transform = torch.tensor(getWorld2View2(R, T, np.array([0,0,0]), 1.0)).transpose(0, 1).cuda()
self.full_proj_transform = (self.world_view_transform.unsqueeze(0).bmm(self.projection_matrix.unsqueeze(0))).squeeze(0)
self.camera_center = self.world_view_transform.inverse()[3, :3]
Colmap camera poses are computed on different flat object, size of images used in this computation is different from size of image I
For example, going from this:
to this after transformation using colmap pose:
