Face retrieval in video sequences using a single face sample

Automatic face retrieval or verification is a matter to identify whether the target person is the same person, which has been received considerable attention by researchers in computer vision. This paper proposes a method to localize a face from video sequences by considering only one shot. First, Cascade AdaBoost is applied to identify region of a face from the video sequence. The image enhancement step is followed in order to reduce the illumination variation. Image enhancement considers facial region’s local mean and standard deviation. Later Singular Value Decomposition (SVD) is used to generate any number of imitated face images for each face by perturbing its n-ordered images. Consequently, the problem of face retrieval with one sample image becomes a common face retrieval problem. In addition, we use the extended t-SNE (t-Distributed Stochastic Neighbour Embedding) to extract condensed facial features. Correspondingly the computation cost is reduced largely. On the basis of the original one facial sample and extended training samples, our proposed method shows a better performance with comparison to other methods. Therefore, the proposed method is effective and competitive. The proposed method can be easily generalized to other face related tasks, such as attribute recognition, general object detection, and face validation.