Appearance Based Recognition Using Spatial and Discriminant Influence

Appearances of objects lie in high-dimensional spaces. For a given recognition task, feature selection aims to select most effective features in order to reduce the recognition cost and improve recognition accuracy. Feature selection can be achieved by a bottom-up scheme, e.g., using spatial information, or a top-down scheme, e.g., using class information. In this paper, we propose a model to integrate spatial and discriminant influence for appearance based recognition, where locality oriented Fisher score is introduced to estimate the discriminant influence. We use Lipschitz regularity to construct image representation. We present a case study of embryo stage recognition to test the performance of the proposed method. We also obtain new insights on the comparison between spatial and discriminant influence.