diff --git a/tools/python/src/correlation_tracker.cpp b/tools/python/src/correlation_tracker.cpp
index 632bd030d..51ca24b23 100644
--- a/tools/python/src/correlation_tracker.cpp
+++ b/tools/python/src/correlation_tracker.cpp
@@ -42,18 +42,18 @@ void start_track_rec (
     start_track(tracker, img, dbounding_box);
 }
 
-void update (
+double update (
     correlation_tracker& tracker,
     object img
 )
 {
     if (is_gray_python_image(img))
     {
-        tracker.update(numpy_gray_image(img));
+        return tracker.update(numpy_gray_image(img));
     }
     else if (is_rgb_python_image(img))
     {
-        tracker.update(numpy_rgb_image(img));
+        return tracker.update(numpy_rgb_image(img));
     }
     else
     {
@@ -61,7 +61,7 @@ void update (
     }
 }
 
-void update_guess (
+double update_guess (
     correlation_tracker& tracker,
     object img,
     const drectangle& bounding_box
@@ -69,11 +69,11 @@ void update_guess (
 {
     if (is_gray_python_image(img))
     {
-        tracker.update(numpy_gray_image(img), bounding_box);
+        return tracker.update(numpy_gray_image(img), bounding_box);
     }
     else if (is_rgb_python_image(img))
     {
-        tracker.update(numpy_rgb_image(img), bounding_box);
+        return tracker.update(numpy_rgb_image(img), bounding_box);
     }
     else
     {
@@ -81,14 +81,14 @@ void update_guess (
     }
 }
 
-void update_guess_rec (
+double update_guess_rec (
     correlation_tracker& tracker,
     object img,
     const rectangle& bounding_box
 )
 {
     drectangle dbounding_box(bounding_box);
-    update_guess(tracker, img, dbounding_box);
+    return update_guess(tracker, img, dbounding_box);
 }
 
 drectangle get_position (const correlation_tracker& tracker) { return tracker.get_position(); }
@@ -100,12 +100,67 @@ void bind_correlation_tracker()
     using boost::python::arg;
     {
     typedef correlation_tracker type;
-    class_<type>("correlation_tracker", "")
-        .def("start_track", &::start_track, (arg("image"), arg("bounding_box")))
-        .def("start_track", &::start_track_rec, (arg("image"), arg("bounding_box")))
-        .def("update", &::update, arg("image"))
-        .def("update", &::update_guess, (arg("image"), arg("guess")))
-        .def("update", &::update_guess_rec, (arg("image"), arg("guess")))
-        .def("get_position", &::get_position);
+    class_<type>("correlation_tracker", "This is a tool for tracking moving objects in a video stream.  You give it \n\
+            the bounding box of an object in the first frame and it attempts to track the \n\
+            object in the box from frame to frame.  \n\
+            This tool is an implementation of the method described in the following paper: \n\
+                Danelljan, Martin, et al. 'Accurate scale estimation for robust visual \n\
+                tracking.' Proceedings of the British Machine Vision Conference BMVC. 2014.")
+        .def("start_track", &::start_track, (arg("image"), arg("bounding_box")), "\
+            requires \n\
+                - image is a numpy ndarray containing either an 8bit grayscale or RGB image. \n\
+                - bounding_box.is_empty() == false \n\
+            ensures \n\
+                - This object will start tracking the thing inside the bounding box in the \n\
+                  given image.  That is, if you call update() with subsequent video frames \n\
+                  then it will try to keep track of the position of the object inside bounding_box. \n\
+                - #get_position() == bounding_box")
+        .def("start_track", &::start_track_rec, (arg("image"), arg("bounding_box")), "\
+            requires \n\
+                - image is a numpy ndarray containing either an 8bit grayscale or RGB image. \n\
+                - bounding_box.is_empty() == false \n\
+            ensures \n\
+                - This object will start tracking the thing inside the bounding box in the \n\
+                  given image.  That is, if you call update() with subsequent video frames \n\
+                  then it will try to keep track of the position of the object inside bounding_box. \n\
+                - #get_position() == bounding_box")
+        .def("update", &::update, arg("image"), "\
+            requires \n\
+                - image is a numpy ndarray containing either an 8bit grayscale or RGB image. \n\
+                - get_position().is_empty() == false \n\
+                  (i.e. you must have started tracking by calling start_track()) \n\
+            ensures \n\
+                - performs: return update(img, get_position())")
+        .def("update", &::update_guess, (arg("image"), arg("guess")), "\
+            requires \n\
+                - image is a numpy ndarray containing either an 8bit grayscale or RGB image. \n\
+                - get_position().is_empty() == false \n\
+                  (i.e. you must have started tracking by calling start_track()) \n\
+            ensures \n\
+                - When searching for the object in img, we search in the area around the \n\
+                  provided guess. \n\
+                - #get_position() == the new predicted location of the object in img.  This \n\
+                  location will be a copy of guess that has been translated and scaled \n\
+                  appropriately based on the content of img so that it, hopefully, bounds \n\
+                  the object in img. \n\
+                - Returns the peak to side-lobe ratio.  This is a number that measures how \n\
+                  confident the tracker is that the object is inside #get_position(). \n\
+                  Larger values indicate higher confidence.")
+        .def("update", &::update_guess_rec, (arg("image"), arg("guess")), "\
+            requires \n\
+                - image is a numpy ndarray containing either an 8bit grayscale or RGB image. \n\
+                - get_position().is_empty() == false \n\
+                  (i.e. you must have started tracking by calling start_track()) \n\
+            ensures \n\
+                - When searching for the object in img, we search in the area around the \n\
+                  provided guess. \n\
+                - #get_position() == the new predicted location of the object in img.  This \n\
+                  location will be a copy of guess that has been translated and scaled \n\
+                  appropriately based on the content of img so that it, hopefully, bounds \n\
+                  the object in img. \n\
+                - Returns the peak to side-lobe ratio.  This is a number that measures how \n\
+                  confident the tracker is that the object is inside #get_position(). \n\
+                  Larger values indicate higher confidence.")
+        .def("get_position", &::get_position, "returns the predicted position of the object under track.");
     }
 }