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peopleDetectorACF

Detect people using aggregate channel features

Description

detector = peopleDetectorACF returns a pretrained upright people detector using aggregate channel features (ACF). The detector is an acfObjectDetector object, and is trained using the INRIA person data set.

example

detector = peopleDetectorACF(name) returns a pretrained upright people detector based on the specified model name.

Examples

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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')

Figure contains an axes object. The hidden axes object with title Detected People and Detection Scores contains an object of type image.

Input Arguments

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ACF classification model, specified as 'inria-100x41' or 'caltech-50x21'. The 'inria-100x41' model was trained using the INRIA Person data set. The 'caltech-50x21' model was trained using the Caltech Pedestrian data set.

Output Arguments

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Trained ACF-based object detector, returned as an acfObjectDetector object. The detector is trained to detect upright people in an image.

References

[1] 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.

[2] 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.

[3] Dollar, P., C., Wojek, B. Shiele, and P. Perona. "Pedestrian Detection: A Benchmark." IEEE Conference on Computer Vision and Pattern Recognition. 2009.

Version History

Introduced in R2017a