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Even if facial expression analysis from 2D luminance images is the present mainstream, it has problems due to changes in facial pose and lighting. In this paper, we use 3D range images which do not maintain such problems for facial expression analysis. We first apply the subspace method to range and luminance images, and clarify their differences in image characteristics. Examining the validity of range images for facial expression analysis, we consider improvement in correct classification rates by integrating results from range and luminance images. We employ the linear combination for their integration and show experimental results.