The Pedestrian Detector is an HOG/SVM-based pedestrian detection IP core, developed for vision-based embedded applications. The algorithm follows a discriminative approach. It combines a HOG-based descriptor and a SVM classifier. HOG (Histogram of Oriented Gradients) is a descriptor designed to encode pedestrian structure. SVM (Support Vector Machine) is a non probabilistic binary linear classifier. The Pedestrian Detector works at a single scale, i.e. the classifier is trained to recognize pedestrian at a fixed size. Extension to multiple scales is given by inserting the core in a framework that provides it with a sequence of re-scaled versions of the same input frame. In this way it is possible to detect pedestrians moving in an arbitrary range of distance.