Detect people using aggregate channel features
returns a pretrained
upright people detector using aggregate channel features (ACF). The detector is an
detector = peopleDetectorACF
acfObjectDetector object, and is
trained using the INRIA person data set.
Detect People Using Aggregated Channel Features
Load the upright people detector.
detector = peopleDetectorACF;
Read an image. Detect people in the image.
I = imread('visionteam1.jpg'); [bboxes,scores] = detect(detector,I);
Annotate detected people with bounding boxes and their detection scores.
I = insertObjectAnnotation(I,'rectangle',bboxes,scores); figure imshow(I) title('Detected People and Detection Scores')
name — ACF classification model
'inria-100x41' (default) |
ACF classification model, specified as
'inria-100x41' model was trained using the
INRIA Person data set. The
was trained using the Caltech Pedestrian data set.
detector — Trained ACF-based object detector
Trained ACF-based object detector, returned as an
acfObjectDetector object. The
detector is trained to detect upright people in an image.
 Dollar, P., R. Appel, S. Belongie, and P. Perona. "Fast Feature Pyramids for Object Detection." IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 36, Issue 8, 2014, pp. 1532–1545.
 Dollar P., C. Wojek, B. Shiele, and P. Perona. "Pedestrian Detection: An Evaluation of the State of the Art." IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 34, Issue 4, 2012, pp. 743–761.
 Dollar, P., C., Wojek, B. Shiele, and P. Perona. "Pedestrian Detection: A Benchmark." IEEE Conference on Computer Vision and Pattern Recognition. 2009.
Introduced in R2017a