College of Arts, Guilin University of Technology, Guilin, Guangxi, China.
College of Design and Media Entertainment, Hanseo University, Seosan-si, Chungcheongnam-do, Korea.
PLoS One. 2020 Dec 28;15(12):e0244205. doi: 10.1371/journal.pone.0244205. eCollection 2020.
In view of the high homogeneity of tourism products all over the country, an attempt is made to design virtual visit tourism products with cultural experience background, which can reflect the characteristics of culture + tourism in different scenic spots, so that tourists can deeply experience the local culture. Combined with computer aided design (CAD), the virtual three-dimensional (3D) modeling system of scenic spots is designed, and VR real scene visit interactive tourism products suitable for different scenic spots are designed. 360° VR panoramic display technology is used for 360° VR panoramic video shooting and visiting system display production of Elephant Trunk Hill park scenery. A total of 157 images are collected and 720 cloud panoramic interactive H5 tool is selected to produce a display system suitable for 360° VR panoramic display of scenic spots. Meanwhile, based on single view RGB-D image, the latest convolutional neural network (CNN) algorithm and point cloud processing algorithm are used to design the indoor 3D scene reconstruction algorithm based on semantic understanding. Experiments show that the pixel accuracy and mean intersection over union of the indoor scene layout segmentation network segmentation results are 89.5% and 60.9%, respectively, that is, it has high accuracy. The VR real scene visit interactive tourism product can make tourists have a more immersive sense of interaction and experience before, during and after the tour.
鉴于全国各地旅游产品同质化程度较高,尝试设计具有文化体验背景的虚拟参观旅游产品,能够体现不同景区的文化+旅游特色,让游客深度体验当地文化。结合计算机辅助设计(CAD),设计景区虚拟三维(3D)建模系统,设计适合不同景区的 VR 实景参观互动旅游产品。采用 360°VR 全景显示技术,对象鼻山公园风景进行 360°VR 全景视频拍摄和参观系统展示制作,共采集 157 张图像,选择 720 云全景互动 H5 工具,制作适合景区 360°VR 全景展示的显示系统。同时,基于单视图 RGB-D 图像,利用最新的卷积神经网络(CNN)算法和点云处理算法,设计基于语义理解的室内 3D 场景重建算法。实验表明,室内场景布局分割网络分割结果的像素准确率和平均交并比分别为 89.5%和 60.9%,即准确率较高。VR 实景参观互动旅游产品可以让游客在游览前、游览中和游览后有更强的互动和体验沉浸感。