'**SUMMARY**
Initializes all the required parameters and attributes of the class.
**PARAMETERS**
* *img* - SimpleCV.Image
* *new_pts* - List of all the tracking points found in the image. - list of cv2.KeyPoint
* *detector* - SURF detector - cv2.FeatureDetector
* *descriptor* - SURF descriptor - cv2.DescriptorExtractor
* *templateImg* - Template Image (First image) - SimpleCV.Image
* *skp* - image keypoints - list of cv2.KeyPoint
* *sd* - image descriptor - numpy.ndarray
* *tkp* - Template Imaeg keypoints - list of cv2.KeyPoint
* *td* - Template image descriptor - numpy.ndarray
**RETURNS**
SimpleCV.Tracking.TrackClass.SURFTrack object
**EXAMPLE**
>>> track = SURFTracker(image, pts, detector, descriptor, temp, skp, sd, tkp, td)'

def __init__(self, img, new_pts, detector, descriptor, templateImg, skp, sd, tkp, td):

    if (td is None):
        bb = (1, 1, 1, 1)
        self = Track.__init__(self, img, bb)
        return
    if (len(new_pts) < 1):
        bb = (1, 1, 1, 1)
        self = Track.__init__(self, img, bb)
        self.pts = None
        self.templateImg = templateImg
        self.skp = skp
        self.sd = sd
        self.tkp = tkp
        self.td = td
        self.detector = detector
        self.descriptor = descriptor
        return
    if (sd is None):
        bb = (1, 1, 1, 1)
        self = Track.__init__(self, img, bb)
        self.pts = None
        self.templateImg = templateImg
        self.skp = skp
        self.sd = sd
        self.tkp = tkp
        self.td = td
        self.detector = detector
        self.descriptor = descriptor
        return
    np_pts = np.asarray([kp.pt for kp in new_pts])
    (t, pts, center) = cv2.kmeans(np.asarray(np_pts, dtype=np.float32), K=1, bestLabels=None, criteria=((cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_MAX_ITER), 1, 10), attempts=1, flags=cv2.KMEANS_RANDOM_CENTERS)
    max_x = int(max(np_pts[:, 0]))
    min_x = int(min(np_pts[:, 0]))
    max_y = int(max(np_pts[:, 1]))
    min_y = int(min(np_pts[:, 1]))
    bb = ((min_x - 5), (min_y - 5), ((max_x - min_x) + 5), ((max_y - min_y) + 5))
    self = Track.__init__(self, img, bb)
    self.templateImg = templateImg
    self.skp = skp
    self.sd = sd
    self.tkp = tkp
    self.td = td
    self.pts = np_pts
    self.detector = detector
    self.descriptor = descriptor
