rotated face detection

Question

Is there a library for detecting faces that have been rotated in the image plane? Or is there some way in which I could use a cascade for upright face detection with opencv to do it?

Answer 1

Here's a simple one I wrote with Python cv2

It's not the most efficient thing, and it uses the naive way suggested by etarion, but it works fairly well for just normal head tilting (It detect anything from -40 to 40 head tilt, which is roughly as much as you can tilt your head staying upright.

import cv2 from math import sin, cos, radians  camera =  cv2.VideoCapture(0) face = cv2.CascadeClassifier("haarcascade_frontalface_alt2.xml")  settings = {     'scaleFactor': 1.3,      'minNeighbors': 3,      'minSize': (50, 50),      'flags': cv2.cv.CV_HAAR_FIND_BIGGEST_OBJECT|cv2.cv.CV_HAAR_DO_ROUGH_SEARCH }  def rotate_image(image, angle):     if angle == 0: return image     height, width = image.shape[:2]     rot_mat = cv2.getRotationMatrix2D((width/2, height/2), angle, 0.9)     result = cv2.warpAffine(image, rot_mat, (width, height), flags=cv2.INTER_LINEAR)     return result  def rotate_point(pos, img, angle):     if angle == 0: return pos     x = pos[0] - img.shape[1]*0.4     y = pos[1] - img.shape[0]*0.4     newx = x*cos(radians(angle)) + y*sin(radians(angle)) + img.shape[1]*0.4     newy = -x*sin(radians(angle)) + y*cos(radians(angle)) + img.shape[0]*0.4     return int(newx), int(newy), pos[2], pos[3]  while True:     ret, img = camera.read()      for angle in [0, -25, 25]:         rimg = rotate_image(img, angle)         detected = face.detectMultiScale(rimg, **settings)         if len(detected):             detected = [rotate_point(detected[-1], img, -angle)]             break      # Make a copy as we don't want to draw on the original image:     for x, y, w, h in detected[-1:]:         cv2.rectangle(img, (x, y), (x+w, y+h), (255,0,0), 2)      cv2.imshow('facedetect', img)      if cv2.waitKey(5) != -1:         break  cv2.destroyWindow("facedetect") 

Answer 2

Personally, I don't know of a library. But, what I can say is, use an eye detection Haar Cascade, and draw a line between the eyes. Then, you can use the atan function and find the angle by which the head is rotated. (Assuming that the person has both eyes on the same horizontal level when head is not rotated)

deg = atan( (leftEye.y - rightEye.y) / (leftEye.x - rightEye.x) ) 

Once you get this angle, rotate the image you have by negative deg degrees and you should have a face which can be detected using the Haar Cascades.