I wrote a simple script to project 3D points into an image bases on the camera intrinsics and extrintics. But when I have a camera at the origin pointing down the z-axis and a 3D points further down the z-axis it appears to be behind the camera instead of in front of it. Here's my script, I've checked it so many times. 

```
import numpy as np

def project(point, P):
    Hp = P.dot(point)

    if Hp[-1] < 0:
        print 'Point is behind camera'

    Hp = Hp / Hp[-1]
    print Hp[0][0], 'x', Hp[1][0]
    return Hp[0][0], Hp[1][0]

if __name__ == '__main__':

    # Rc and C are the camera orientation and location in world coordinates
    # Camera posed at origin pointed down the negative z-axis
    Rc = np.eye(3)
    C  = np.array([0, 0, 0])

    # Camera extrinsics
    R = Rc.T
    t = -R.dot(C).reshape(3, 1)

    # The camera projection matrix is then:
    # P = K [ R | t] which projects 3D world points 
    # to 2D homogenous image coordinates.

    # Example intrinsics dont really matter ...

    K = np.array([
        [2000, 0,  2000],
        [0,  2000, 1500],
        [0,  0,  1],
    ])

    # Sample point in front of camera
    # i.e. further down the negative x-axis
    # should project into center of image
    point = np.array([[0, 0, -10, 1]]).T

    # Project point into the camera
    P = K.dot(np.hstack((R, t)))

    # But when projecting it appears to be behind the camera?
    project(point,P)

```

The only thing I can think of is that the identify rotation matrix doesn't correspond to the camera pointing down the negative z-axis with the up vector in the direction of the positive y-axis. But I can't see how this wouldn't be the case is for example I had constructed Rc from a function like gluLookAt and given it a camera at the origin pointing down the negative z-axis I would get the identity matrix.