diff --git a/facelib/S3FDExtractor.py b/facelib/S3FDExtractor.py
index 59e42f1..e4753b8 100644
--- a/facelib/S3FDExtractor.py
+++ b/facelib/S3FDExtractor.py
@@ -1,6 +1,9 @@
-import numpy as np
+import operator
 from pathlib import Path
+
 import cv2
+import numpy as np
+
 from nnlib import nnlib
 
 class S3FDExtractor(object):
@@ -19,7 +22,7 @@ class S3FDExtractor(object):
     def __exit__(self, exc_type=None, exc_value=None, traceback=None):
         return False #pass exception between __enter__ and __exit__ to outter level
 
-    def extract (self, input_image, is_bgr=True):
+    def extract (self, input_image, is_bgr=True, is_remove_intersects=False):
 
         if is_bgr:
             input_image = input_image[:,:,::-1]
@@ -45,6 +48,21 @@ class S3FDExtractor(object):
             b += bt*0.1 #enlarging bottom line a bit for 2DFAN-4, because default is not enough covering a chin
             detected_faces.append ( [int(x) for x in (l,t,r,b) ] )
 
+        #sort by largest area first
+        detected_faces = [ [(l,t,r,b), (r-l)*(b-t) ]  for (l,t,r,b) in detected_faces ]
+        detected_faces = sorted(detected_faces, key=operator.itemgetter(1), reverse=True )
+        detected_faces = [ x[0] for x in detected_faces]
+                          
+        if is_remove_intersects:
+            for i in range( len(detected_faces)-1, 0, -1):
+                l1,t1,r1,b1 = detected_faces[i]
+                l0,t0,r0,b0 = detected_faces[i-1]
+
+                dx = min(r0, r1) - max(l0, l1)
+                dy = min(b0, b1) - max(t0, t1)
+                if (dx>=0) and (dy>=0):
+                    detected_faces.pop(i)     
+                 
         return detected_faces
 
     def refine(self, olist):
diff --git a/mainscripts/Extractor.py b/mainscripts/Extractor.py
index 7a626eb..0935596 100644
--- a/mainscripts/Extractor.py
+++ b/mainscripts/Extractor.py
@@ -153,15 +153,11 @@ class ExtractSubprocessor(Subprocessor):
                         elif rot == 270:
                             rotated_image = image.swapaxes( 0,1 )[::-1,:,:]
 
-                        rects = data.rects = self.e.extract (rotated_image, is_bgr=True)
+                        rects = data.rects = self.e.extract (rotated_image, is_bgr=True, is_remove_intersects=True)
                         if len(rects) != 0:
                             break
                         
                     if self.max_faces_from_image != 0 and len(data.rects) > 1:
-                        #sort by largest area first
-                        x = [ [(l,t,r,b), (r-l)*(b-t) ]  for (l,t,r,b) in data.rects]
-                        x = sorted(x, key=operator.itemgetter(1), reverse=True )
-                        x = [ a[0] for a in x]
                         data.rects = x[0:self.max_faces_from_image]
 
                 return data
@@ -893,3 +889,4 @@ def extract_umd_csv(input_file_csv,
     io.log_info ('Images found:        %d' % (images_found) )
     io.log_info ('Faces detected:      %d' % (faces_detected) )
     io.log_info ('-------------------------')
+