diff --git a/examples/tracking/visual/PyCV_TrackFeaturesFwdBck.jl b/examples/tracking/visual/PyCV_TrackFeaturesFwdBck.jl
index 3f98618de..286b7b18e 100644
--- a/examples/tracking/visual/PyCV_TrackFeaturesFwdBck.jl
+++ b/examples/tracking/visual/PyCV_TrackFeaturesFwdBck.jl
@@ -49,7 +49,7 @@ function goodFeaturesToTrack(im1, feature_params; mask=nothing)
   cv.goodFeaturesToTrack(collect(reinterpret(UInt8, im1)), mask=collect(reinterpret(UInt8,mask)), feature_params...)
 end
 
-function goodFeaturesToTrackORB(im1; mask=nothing, orb = cv.ORB_create(), downsample::Int=5, tolerance::Real = 0.1) 
+function goodFeaturesToTrackORB(im1; mask=nothing, orb = cv.ORB_create(), downsample::Int=1, tolerance::Real = 0.1) 
   # gray = cv2.cvtColor(im1,cv.COLOR_BGR2GRAY)
   # kypts, decrs = orb.detectAndCompute(gray,None)
   # https://docs.opencv.org/3.4/d1/d89/tutorial_py_orb.html
@@ -57,9 +57,13 @@ function goodFeaturesToTrackORB(im1; mask=nothing, orb = cv.ORB_create(), downsa
   img = collect(reinterpret(UInt8, im1))
   kp = orb.detect(img, collect(reinterpret(UInt8,mask)))
 
-  # downselect a better distribution of features
-  rows, cols = size(img,1), size(img,2)
-  sel_kp = ssc(kp, orb.getMaxFeatures() ÷ downsample, tolerance, cols, rows)
+  sel_kp = if 1 < downsample
+    # downselect a better distribution of features
+    rows, cols = size(img,1), size(img,2)
+    ssc(kp, orb.getMaxFeatures() ÷ downsample, tolerance, cols, rows)
+  else
+    kp
+  end
 
   # compute the descriptors with ORB
   kp_, des = orb.compute(img, sel_kp)