System object: vision.PeopleDetector
Detect upright people using HOG features
BBOXES = step(peopleDetector,I)
[BBOXES, SCORES] = step(peopleDetector,I)
BBOXES = step(peopleDetector,I) performs multi-scale object detection on the input image, I. The method returns an M-by-4 matrix defining M bounding boxes, where M represents the number of detected people. Each row of the output matrix, BBOXES, contains a four-element vector, [x y width height], that specifies in pixels, the upper-left corner and size of a bounding box. When no people are detected, the step method returns an empty vector. The input image I, must be a grayscale or truecolor (RGB) image.
[BBOXES, SCORES] = step(peopleDetector,I) additionally returns a confidence value for the detections. The M-by-1 vector, SCORES, contain positive values for each bounding box in BBOXES. Larger score values indicate a higher confidence in the detection. The SCORES value depends on how you set the MergeDetections property. When you set the property to true, the people detector algorithm evaluates classification results to produce the SCORES value. When you set the property to false, the detector returns the unaltered classification SCORES.
Note: H specifies the System object™ on which to run this step method.
The object performs an initialization the first time the step method is executed. This initialization locks nontunable properties and input specifications, such as dimensions, complexity, and data type of the input data. If you change a nontunable property or an input specification, the System object issues an error. To change nontunable properties or inputs, you must first call the release method to unlock the object.