Features versus context: An approach for precise and detailed detection and delineation of faces and facial features.

ABSTRACT: The appearance-based approach to face detection has seen great advances in the last several years. In this approach, we learn the image statistics describing the texture pattern (appearance) of the object class we want to detect, e.g., the face. However, this approach has had limited success in providing an accurate and detailed description of the internal facial features, i.e., eyes, brows, nose, and mouth. In general, this is due to the limited information carried by the learned statistical model. While the face template is relatively rich in texture, facial features (e.g., eyes, nose, and mouth) do not carry enough discriminative information to tell them apart from all possible background images. We resolve this problem by adding the context information of each facial feature in the des

SUBMITTER: Ding L 

PROVIDER: S-EPMC3657115 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature