The document discusses implementing and modifying the Histogram of Oriented Gradients (HOG) descriptor algorithm to improve pedestrian detection performance. It implements HOG using OpenCV and trains a support vector machine (SVM) on the INRIA dataset. Various modifications to HOG are tested, including different cell sizes, histogram bin configurations, and levels of Gaussian blur, to determine their effect on detection rate and false positive rate. The best performance is achieved with 9 signed histogram bins, small cell sizes, and no Gaussian blur.