Active energy image plus 2DLPP for gait recognition

This paper proposes a novel active energy image (AEI) method for gait recognition. Existing human gait feature representation methods, however, usually suffer from low quality of human silhouettes and insufficient dynamic characteristics. To this end, we apply the proposed AEI for gait representation. Given a gait silhouette sequence, we first extract the active regions by calculating the difference of two adjacent silhouette images, and construct an AEI by accumulating these active regions. Then, we project each AEI to a low-dimensional feature subspace via the newly proposed two-dimensional locality preserving projections (2DLPP) method to further improve the discriminative power of the extracted features. Experimental results on the CASIA gait database (dataset B and C) demonstrate the effectiveness of the proposed method.