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Summary 5G virtual reality technology is a technology that has attracted widespread attention in the computer field in recent years. Establishing a harmonious human–computer interaction environment in the multidimensional information space is one of the development goals of information technology. Face information is important information for identifying the identity of others. Three‐dimensional information has important applications in many fields and directions of machine vision. Therefore, the three‐dimensional common face image has a significant meaning. In this paper, binocular stereo vision system is used to collect multiple pairs of facial information images. The image correction method was used to correct the collected image pairs. According to the basic criteria of stereo matching, the advantages and disadvantages of various traditional image matching methods are analyzed. On the basis of completing the image correction, the graph cut matching method is selected as the matching method, and multiple pairs of collected image pairs are matched by this method to obtain a multi‐angle face disparity map. In this paper, after studying the basic dense matching algorithm and its improved algorithm, the SAD, SD, and NC methods of fixed window are used to compare the matching cost and the performance of the adaptive weight method in face matching. This paper studies the virtual roaming technology and the basis of the related Internet of Things (IoT) 3D face graphics theory and develops a building virtual roaming system based on MFC and OpenGL. The system draws on the basic I/0 device of the computer and provides users with a friendly MFC interface and multiple viewing angles and multiple roaming mode options for virtual faces. Experimental research shows that the reconstruction accuracy of the spatial points of the reconstructed face and the actual situation are both about 1%, which shows that the IoT 3D face modeling algorithm designed in this paper has high accuracy.

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