# Special Issue on \"Augmented Reality, Virtual Reality & Semantic 3D Reconstruction\"
## 2 Augmented Reality, Virtual Reality and Semantic 3D Reconstruction  
As highly immersive virtual reality (VR) content, 360\({}^{\circ}\) video allows users to observe all viewpoints within the desired direction from the position where the video is recorded. In 360\({}^{\circ}\) video content, virtual objects are inserted into recorded real scenes to provide a higher sense of immersion. [PERSON] et al. [1] propose a new method for previsualization and 3D composition that overcomes the limitations of existing methods. This system achieves real-time position tracking of the attached camera using a ZED camera and a stereovision sensor, and real-time stabilization using a Kalman filter. The proposed system shows high time efficiency and accurate 3D composition. Dynamic hand gesture recognition based on one-shot learning requires full assimilation of the motion features from a few annotated data. However, how to effectively extractthe spatio-temporal features of the hand gestures remains a challenging issue. [PERSON] et al. [2] propose a skeleton-based dynamic hand gesture recognition using an enhanced network (GREN) based on one-shot learning by improving the memory-augmented neural network, which can rapidly assimilate the motion features of dynamic hand gestures. Besides, the network effectively combines and stores the shared features between dissimilar classes, which lowers the prediction error caused by unnecessary hyperparameters updating, and improves the recognition accuracy with the increase of categories. The experimental results demonstrate that the GREN network is feasible for skeleton-based dynamic hand gesture recognition based on one-shot learning. Human cognitive processes in wayfinding may differ depending on the time taken to accept visual information in environments. [PERSON] [3] investigated users' wayfinding processes using eye-tracking experiments, simulating a complex cultural space to analyze human visual movements in perception and the cognitive processes through visual perception responses. The results show that the methods for analyzing the gaze data may vary in terms of processing, analysis, and scope of the data depending on the purpose of the virtual reality experiments. Further, they demonstrate the importance of what purpose statements are given to the subject during the experiment and the possibility of a technical approach being used for the interpretation of spatial information. Ref. [4] report concerns a study of the impact of a semi-immersive VR system in a group of 25 children in a kindergarten context. The children were involved in several different games and activity types. Their reactions and behaviors were recorded through observation grids addressing task comprehension, participation and enjoyment, interaction and cooperation, conflict, strategic behaviors, and adult-directed questions concerning the activity, the device or general help requests. The grids were compiled at the initial, intermediate and final timepoint during each session. The results show that the activities are easy to understand, enjoyable, and stimulate strategic behaviors, interaction and cooperation, while they do not elicit the need for many explanations. These results are discussed within a neuroconstructivist educational framework and the suitability of semi-immersive, virtual-reality-based activities for cognitive empowerment and rehabilitation purposes is discussed. As a classical method widely used in 3D reconstruction tasks, the multisource Photometric Stereo can obtain more accurate 3D reconstruction results compared with the basic Photometric Stereo, but its complex calibration and solution process reduces the efficiency of this algorithm. [PERSON] et al. [5] propose a multisource Photometric Stereo 3D reconstruction method based on the fully convolutional network (FCN). The experimental results show that their method has a good effect on solving the main problems faced by the classical method.