1. A method for detecting crowd density, the method comprising: projecting a depth image obtained by photographing onto a height-top-view, the depth image including a crowd; dividing the height-top-view into cells with a predetermined size; for each respective cell of the cells, extracting a density detection feature indicating distribution of differences in height between pixels in the cell; and detecting, based on the density detection feature, using a density model previously constructed by a statistical learning method, number of persons in each of the cells, wherein the density detection feature is a Local binary pattern (LBP) feature based on a height, and wherein the extracting of the density detection feature for each respective cell, and for each respective pixel in the cell, includes determining adjacent pixels around the respective pixel as a center, whose distance from the respective pixel is a predetermined distance, comparing a pixel value of the respective pixel and a pixel value of each of the respective adjacent pixels and if a difference between the pixel value of a respective one of the adjacent pixels and the pixel value of the respective pixel is less than a first threshold and the pixel value of the respective one of the adjacent pixels is greater than a second threshold, then allocating 1 to a value of the respective one of the adjacent pixels, and if not, then allocating 0 to the value of the respective one of the adjacent pixels, and setting a binary code composed of the values of the adjacent pixels as a LBP code of the pixel.