In order to realize the optimal management of power customers in the smart power management system，it is necessary to construct a stereoscopic image of the power customer，and propose a power customer stereoscopic image construction method based on multi-dimensional category feature recognition and corner point identification. The user portrait information tracking acquisition model uses the spatial feature domain classification method to classify the user image information，and uses the multi-scale layer-by-layer analysis method to accurately locate the fuzzy power customer image，and extracts the power category feature quantity of the customer stereo image，using the feature domain. The classification and block matching method performs error repair of the stereo image to realize fast and accurate positioning of the features of the user image. The support demand vector machine learning algorithm is used to adaptively classify the extracted power demand feature of the power customer stereo image，and realize the multi-dimensional construction of the power customer stereo image in the smart power management system. The results show that the method of constructing the power customer stereo image has better feature segmentation ability and the customer stereo image information has high accuracy.