Virtual simulation and 3D interaction have shown great potentials in a variety of domains for our future life. For a virtual fish swarm simulation system, the simulation of cohesion behaviors of fish swarm and the interaction between human and fish swarm are two key components to create immersive interactive experiences. However, it is a huge challenge to create a realistic fish swarm simulation system while providing a natural and comfortable interaction. In this paper, we propose a method for immersive virtual fish swarm simulation based on infrared sensors. Based on dynamic weight constraints, we propose a particle swarm optimization method for fish swarm cohesion simulation, which separates a particle swarm by the state of each particle and dynamically controls the particle swarm, making the movement behavior of virtual fish more realistic. In addition, an interactive fast skinning method is proposed for cartoon fishes, which leverages image segmentation, Optical Character Recognition (OCR) and bone skinning are used to generate cartoon fishes based on user-created colors. With infrared sensors, we propose a method for virtual fish swarm interaction, where the positions of human skeleton are processed by an action analyzer, achieving real-time user interactions with fish swarms. With all the proposed techniques integrated in a system, the experimental results show that our method is feasible and effective.
Peking opera is one of the national cultural heritages in China. However, it is difficult for people to learn the gestures in Peking opera performance, which limits the spread of this traditional culture. To address this issue, we propose a Peking opera gesture training system using infrared sensors. Specifically, we build a character avatar for demonstrating the gestures in Peking opera in the proposed system. Based on the data collected by infrared sensors, a method for calculating gesture similarity is proposed and is applied for the training of Peking opera gestures, which allows natural interactions and provides interactive feedback for user gestures. We conducted multiple experiments to verify the feasibility and effectiveness of the training system. The experimental results showed that the proposed system can overcome the difficulties in the traditional learning process of Peking opera gestures, which helps users to achieve the goal of learning standard Peking opera gestures. The proposed training system greatly eases the learning of Peking opera gestures, adding vitality into the culture of traditional Peking opera.
Terrain synthesis has been a hot topic in the field of computer graphics and image processing. However, there are still issues in terrain synthesis where synthesis results are difficult to control and not realistic enough. To address these problems, this paper proposes an interactive terrain elevation map generation method based on the synthesis of a single sample terrain elevation map. First, we propose a method to extract the skeleton from a terrain elevation map and a user sketch. Second, we construct a skeleton sample feature map based on the terrain elevation map and the user sketch. Finally, we propose a matching cost function to match image patches of the terrain sample and the user sketch. The proposed method can obtain a synthesis result containing the features of both the terrain sample and the user sketch, and then generates a synthetic terrain elevation map. The experimental results demonstrate the effectiveness of the proposed method, where the synthesized results can meet the needs of users.
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