Research on role modeling and behavior control of virtual reality animation interactive system in Internet of Things

Abstract

To solve the problems of poor real-time collision accuracy and low efficiency of modeling in the virtual reality environment, we propounded a depth image-based 3D modeling system and a hybrid intelligent collision detection algorithm. With the development of the 3D animation interactive system as an example, this paper uses 3D modeling technology based on depth images to build single role models, then reorganizes and merges the models to form 3D scenes. The hybrid intelligent collision detection algorithm, which combines the quantum behavior particle swarm optimization algorithm and the differential algorithm, improves the collision detection efficiency and accuracy and realizes behavior control of the characters in the interactive system. The experimental result shows that the 3D modeling technology based on depth images has greatly improved the accuracy and quantity of model texture and motion rate. By comparing the hybrid intelligent collision detection algorithm, the QPSO algorithm, and the FDH bounding box for collision detection, we conclude that the algorithm used in this paper has a shorter average collision time, more stable role behavior control, and better robustness.