calcOpticalFlowPyrLK losing single user-defined tracking point

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I am trying to write a python program to track a user's head movement based on a single point between their eyes. I am using OpenCV 2.4.5 and calcOpticalFlowPyrLK. I set the initial point using HAAR points, and the initial point is correct, but after the first call to calcOpticalFlowPyrLK the program is now tracking a completely different point. I'm not very familiar with computer vision, so I can't figure out why its losing the initial point.

I'm using python 2.7, Fedora 18, and OpenCV 2.4.5.

My code:

import numpy as np
import cv2

cap = cv2.VideoCapture(0)

# loading the classifiers
hcf = cv2.CascadeClassifier('/usr/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml')
hce = cv2.CascadeClassifier('/usr/share/OpenCV/haarcascades/haarcascade_eye.xml')

# params for ShiTomasi corner detection
feature_params = dict( maxCorners = 100,
                       qualityLevel = 0.3,
                       minDistance = 7,
                       blockSize = 7 )

# Parameters for lucas kanade optical flow
lk_params = dict( winSize  = (15,15),
                  maxLevel = 2,
                  criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))

# Create some random colors
color = np.random.randint(0,255,(100,3))

# Take first frame and find corners in it
ret, old_frame = cap.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)

# Create a mask image for drawing purposes
mask = np.zeros_like(old_frame)

first = True
while(1):
    #Get new frame
    ret,frame = cap.read()
    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    #First iteration, calcualte the face
    if(first):
        first = False
        faces = hcf.detectMultiScale(frame_gray, minSize=(100, 100))
        face = faces[0]
        print face[0],face[1],face[2],face[3]

        p0 = [[((face[0] + (face[2]/2)),(face[1] + (face[3]/3)))]]
        p0 = np.float32(np.asarray(p0))
        print "p0", p0

    #cv2.rectangle(frame,(face[0], face[1]), (face[0] + face[2], face[1] + face[3]),(155, 255, 25),2)
    #Draw circle at initial point
    cv2.circle(frame,((face[0] + (face[2]/2)),(face[1] + (face[3]/3))),5,(155, 255, 25))

    # calculate optical flow
    p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)

    # Select good points
    if st==1:
        good_new = p1[st==1]
        good_old = p0[st==1]

        # draw the tracks
        for i,(new,old) in enumerate(zip(good_new,good_old)):
            a,b = new.ravel()
            c,d = old.ravel()
            mask = cv2.line(mask, (a,b),(c,d), color[i].tolist(), 2)
            cv2.circle(frame,(a,b),5,color[i].tolist(),-1)

    cv2.imshow('frame',frame)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break

    # Now update the previous frame and previous points
    old_gray = frame_gray.copy()
    if st==1:
        p0 = good_new.reshape(-1,1,2)

cv2.destroyAllWindows()
cap.release()