Face image retrieval by using Haar features

We propose a new method to retrieve similar face images from large face databases. The proposed method extracts a set of Haar-like features, and integrates these features with supervised manifold learning. Haar-like features are intensity-based features. The values of various Haar-like features comprise our rectangle feature vector (RFV) to describe faces. Compared with several popular unsupervised dimension reduction methods, RFV is more effective in retrieving similar faces. To further improve the performance, we combine RFV and a supervised manifold learning method and obtain satisfactory retrieval results.