In today’s society, information technology is widely used, and virtual reality technology, as one of the emerging frontier technologies, has entered a stage of rapid development. Virtual reality is the use of computer technology to simulate the real-life environment into a virtual simulation environment, with the help of special equipment to realize the natural interaction between users and technical environment, in which the tourism industry is the most widely used. In order to realize 3D virtual reality of tourist attractions and improve users’ immersive experience in the process of interaction, the deep belief neural network is introduced to realize the target recognition and reconstruction in virtual reality. The results show that the algorithm has excellent performance in target recognition and target reconstruction, and deep belief networks improve the accuracy by 0.57% and 0.81% and the accuracy by 0.21% and 2.06%, respectively, compared with the current optimal algorithm in target recognition of 12 and 20 view regular projection images. Compared with the current optimal algorithm, deep belief networks are reduced by 0.2%, 3.7%, and 0.6%, respectively. The accuracy index was increased by 2%, 0.1%, and 0.1%, respectively. The above results show that the proposed algorithm based on the deep belief neural network can realize 3D virtual reality of complex scenes such as tourist attractions according to its excellent performance.

中文翻译：

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基于深度置信神经网络的旅游景点3D虚拟现实实现

当今社会，信息技术广泛应用，虚拟现实技术作为新兴前沿技术之一，已进入快速发展阶段。虚拟现实是利用计算机技术将现实生活环境模拟成虚拟仿真环境，借助专用设备实现用户与技术环境的自然交互，其中在旅游业应用最为广泛。为了实现旅游景点的3D虚拟现实，提高用户在交互过程中的沉浸式体验，引入深度置信神经网络实现虚拟现实中的目标识别与重建。结果表明，该算法在目标识别和目标重建方面具有优异的性能，与当前目标识别最优算法相比，深度置信网络准确率分别提高了0.57%和0.81%，准确率分别提高了0.21%和2.06% 12 和 20 视图常规投影图像。与当前最优算法相比，深度置信网络分别减少了0.2%、3.7%和0.6%。准确率指数分别提高了2%、0.1%和0.1%。上述结果表明，所提出的基于深度置信神经网络的算法以其优异的性能能够实现旅游景点等复杂场景的3D虚拟现实。