Fusion of depth and color for an improved active shape model
Active Shape Models (ASMs) have been widely used in facial feature representation and related applications. In this paper, we exploit the availability of registered depth and color information from a low resolution camera sensor to improve Active Shape Model fitting accuracy and efficiency. Two independent Active Shape Model profile models are constructed based on the gradient profiles of depth and color intensity information. These two channels are fused using full or partial depth information. The algorithm determines the optimal point localization using the color/depth profiles during the update step of the ASM fitting process. Results show improvements in accuracy over standard methods using color intensity or depth information alone.