The present invention provides a multi-scale feature estimation and high-order BING feature-based target detection method. The method includes the following steps that: an image feature pyramid is constructed for an original image by using an existing multi-scale histogram of oriented gradient approximation algorithm; high-order BING features are extracted in each histogram of oriented gradient; each window in sliding windows is judged by using a two-stage linear SVM; and whether the windows contain a target is determined. According to the method of the invention, the BING features are expanded to the histograms of oriented gradient from simple gradient features, wherein the histograms of oriented gradient can show more details of the features, high-order statistical information is extracted, and therefore, feature expressions can be richer; and when the feature pyramid is calculated, the multi-scale histogram of oriented gradient approximation algorithm is adopted, and therefore, a more detailed feature pyramid can be obtained under a condition that calculation quantity is not increased, and the position of the detected target is more accurate.