How To Detect Pedestrians with NXP Vision Toolbox

Daniel_Popa — Wed, 20 Jun 2018 17:32:47 GMT

Pedestrian detection

The following livescript uses MATLAB functionalities to simulate the pedestrian detection application. The pedestrian detection algorithm is implemented using Histogram of Oriented Gradients (HOG) and a linear Support Vector Machine (SVM).

Create a People Detector object with general Classification Model.

detector = vision.PeopleDetector('ClassificationModel', 'UprightPeople_96x48', 'ClassificationThreshold', 2.5);

Read the input image which can be RGB or grayscale.

inImgUMat = nxpvt.imread('data/img_sdk.png');

if isempty(inImgUMat)

fprintf('Failed to open input image: %s.', inImgPath);

return;

end

nxpvt.imshow(inImgUMat);

If the input image if RGB transform if to grayscale.

inImgUMatGray = nxpvt.apexcv.rgb2gray(inImgUMat);

nxpvt.imshow(inImgUMatGray);

Run the pedestrian detector on the grayscale image.

bboxes = step(detector, inImgUMatGray.getData());

Add the resulted information on the original image.

outImgUMat = nxpvt.cv.rectangle(inImgUMat, bboxes, [255, 0 ,0], 5);

nxpvt.imshow(outImgUMat);

MBDT for VISION中的主题 How To Detect Pedestrians with NXP Vision Toolbox

How To Detect Pedestrians with NXP Vision Toolbox

Pedestrian detection