Abstract
In this paper, a pedestrian detection system which uses sliding window approach to detect pedestrians in still digital images is presented. The proposed pedestrian detection system combines weak classifiers in an Adaboost like novel way to create a strong classifier. Besides, rectangle ratios and discrete cosine transform coefficients are used as features with the well-known rectangle differences method.
Keywords
Pedestrian detection
Rectangle
Artificial intelligence
AdaBoost
Computer science
Pedestrian
Computer vision
Pattern recognition (psychology)
Classifier (UML)
Object detection
Sliding window protocol
Discrete cosine transform
Window (computing)
Mathematics
Engineering
Image (mathematics)
Subject Areas
Video Surveillance and Tracking Methods
·Computer Vision and Pattern Recognition ·Physical Sciences
Face and Expression Recognition
·Computer Vision and Pattern Recognition ·Physical Sciences
Remote-Sensing Image Classification
·Media Technology ·Physical Sciences
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