Integral Channel Features is an object detection framework that takes advantadge of the richness of information present in distinct channels of an image. By extracting and evaluating a large number of features from each detection window, a trained boosted classifier is able to perform classification. This work uses this algorithm for pedestrian detection.
An explanation of how to use the developed work, as well as an overview of all the source files is provided in this documentation.
