[OpenCV] What do the "left" and "right" values mean in the haar cascade xml files?

Question

In OpenCV's haar cascade files, what are the "left" and "right" values, and how does this refer to the "threshold" value? Thanks!

Just for reference, here's the structure of the files:

<haarcascade_frontalface_alt type_id="opencv-haar-classifier">
  <size>20 20</size>
  <stages>
    <_>
      <!-- stage 0 -->
      <trees>
        <_>
          <!-- tree 0 -->
          <_>
            <!-- root node -->
            <feature>
              <rects>
                <_>3 7 14 4 -1.</_>
                <_>3 9 14 2 2.</_></rects>
              <tilted>0</tilted></feature>
            <threshold>4.0141958743333817e-003</threshold>
            <left_val>0.0337941907346249</left_val>
            <right_val>0.8378106951713562</right_val></_></_>
        <_>

Answer 1

The "left" and "right" refer to the gradient values of a particular shape. These particular shapes are not specifically a left rectangle and a right rectangle. Instead, it just refers to sections of a particular configuration (sometimes more than one section if there are more than 2). There is a diagram in the David Haar paper which helps explain this.

Here is an ascii representation (= is filled, - unfilled):

====    ==--   =--=
====    ==--   =--=
----    ==--   =--=
----    ==--   =--=

Overall, the naming is bad convention. Instead, it should be named "gradient top", "gradient bottom" (2), "gradient left", "gradient right" (2), "gradient left", "gradient center", "gradient bottom" (3), respectively. Rotated, edge, and other shapes should be named to uniquely identify the sections.

Answer 2

i am not understand how u written this code 20 20 <> <> <> <>3 7 14 4 -1. <>3 9 14 2 2. 0 4.0141958743333817e-003 0.0337941907346249 0.8378106951713562 <>

Answer 3

Thanks for the answer.

What is the David Haar paper?

Answer 4

To my understanding, the original article is Rapid Object Detection using a Boosted Cascade of Simple Features by Paul Viola and Michael Jones. It is based upon Haar-like features, hence the name. I suggest grabbing it from the IEEE website. (If you don't have an account, check the other versions on Google Scholar.)

The classifiers are also described in Facial feature detection using Haar classifiers (Wilson, Fernandez). You can find it on the ACM website or on the CSA website.

Answer 5

In the source code of OpenCV, you will find cvhaar.cpp that gives some insight into how Haar cascade works. Unfortunately, this is essentially no commentary, nor does the documentation help much. Here's my understanding of how it works.

In the function icvEvalHidHaarClassifier(), the sum is computed for the the features of a single CvHidHaarTreeNode.

If this sum is less than the threshold, the "left" node is followed, and the process is repeated. Otherwise, the "right" node is followed, again repeating. This is reflected by the following statement:

idx = sum < t ? node->left : node->right;

The loop is broken when the "left" or "right" node is a negative value. In this case, the sum is no longer computed for this feature, but the threshold value for that feature is returned as the result of the classifier.

I put "left" and "right" in quotes because, as you say, they have nothing to do with the feature position. Instead, they reflect which way the cascade "falls": below the threshold, the cascade falls left, above the threshold, it falls right.

Let us now step back to the representation of these nodes. In the XML, you will see the representation of the nodes not as indexes, but as values:

<left_val>0.0337941907346249</left_val>
<right_val>0.8378106951713562</right_val>

These numbers are in fact node names that are looked up using cvGetFileNodeByName(). I don't know exactly how this works inside OpenCV, but now I hope you at least have a better idea how the cascade works.

Answer 6

what does left_node1/left_node and right_node1/right_node means? i saw it in lot's of classifiers downloaded from the internet but i can't understand what does they mean.