What is scale factor in face recognition?
The scale factor specifies how the image size is modified at each image scale, thus the model has a fixed size for training. If the factor is small, the detection could be slow as it is more precise. If the factor is large, the detection could miss some faces.
What is scale factor in cascade classifier?
The argument scaleFactor determines the factor by which the detection window of the classifier is scaled down per detection pass (see video above). A factor of 1.1 corresponds to an increase of 10%. Hence, increasing the scale factor increases performance, as the number of detection passes is reduced.
What is detectMultiScale in OpenCV?
detectMultiScale function is used to detect the faces. This function will return a rectangle with coordinates(x,y,w,h) around the detected face. It takes 3 common arguments — the input image, scaleFactor, and minNeighbours. scaleFactor specifies how much the image size is reduced with each scale.
What is minNeighbors OpenCV?
minNeighbors – Parameter specifying how many neighbors each candidate rectangle should have to retain it. In other words, this parameter will affect the quality of the detected faces. Higher value results in less detections but with higher quality.
What is Cascade in OpenCV?
It is a machine learning based approach where a cascade function is trained from a lot of positive and negative images. It is then used to detect objects in other images.
What is a Haar cascade classifier?
Haar Cascade is a machine learning-based approach where a lot of positive and negative images are used to train the classifier. Positive images – These images contain the images which we want our classifier to identify. Negative Images – Images of everything else, which do not contain the object we want to detect.
How does Haar Cascade detect eye?
The Haar cascade classifier is an effective way to detect various objects in the surroundings. This method is also used in detection of face and eyes. The main objective of the Haar cascade classifier is a collection a of a lot of positive images and negative images which are later on to train the classifier.
What is winStride?
The winStride parameter is a 2-tuple that dictates the “step size” in both the x and y location of the sliding window. Both winStride and scale are extremely important parameters that need to be set properly.
Which is best algorithm for face detection?
Algorithm 1: OpenCV Haar Cascade Face Detection This face detector was introduced in 2001 and remained the state-of-the-art face detection algorithm for many years. Other than just this face detector, OpenCV provides some other detectors (like eye, and smile, etc) too, which use the same haar cascade technique.
Is Haar Cascade fast?
Some Haar cascade benefits are that they're very fast at computing Haar-like features due to the use of integral images (also called summed area tables). They are also very efficient for feature selection through the use of the AdaBoost algorithm.
How accurate are Haar Cascades?
By using Equation (3) Accuracy is obtained for the Haar cascade is 96.24% and for LBP classifier 94.74%.
Can Haar Cascade detect multiple faces?
Some of them have a single side of the face visible, so the Haar model did not detect anything. Some of them have multiple faces detected as there more than one person in the images. In some of them, the model detects a tie as a face, or it detects only one eye in one of them.
Example
The following program demonstrates how to apply scale transformation to an image.
Output
If you open the specified path, you can observe the output image as follows (size − Width:600px and height:600px) −
Definition
Some information relates to prerelease product that may be substantially modified before it’s released. Microsoft makes no warranties, express or implied, with respect to the information provided here.
Remarks
This element specifies the view scaling factors that the presentation was last viewed with.
What is numDetections vector?
Vector of detection numbers for the corresponding objects. An object's number of detections is the number of neighboring positively classified rectangles that were joined together to form the object.
What is a vector of rectangles?
Vector of rectangles where each rectangle contains the detected object, the rectangles may be partially outside the original image. Parameter specifying how much the image size is reduced at each image scale. Parameter specifying how many neighbors each candidate rectangle should have to retain it.
