In this paper we present a framework for the rendering of dynamic 3D virtual environments which can be integrated in the development of videogames. It includes methods to manage sounds and particle effects, paged static geometries, the support of a physics engine and various input systems. It has been designed with a modular structure to allow future expansions. We exploited some open-source state-of-the-art components such as OGRE, PhysX, ParticleUniverse, etc.; all of them have been properly integrated to obtain peculiar physical and environmental effects. The stand-alone version of the application is fully compatible with Direct3D and OpenGL APIs and adopts OpenAL APIs to manage audio cards. Concluding, we devised a showcase demo which reproduces a dynamic 3D environment, including some particular effects: the alternation of day and night influencing the lighting of the scene, the rendering of terrain, water and vegetation, the reproduction of sounds and atmospheric agents.
In the area of environmental effects simulation, several methods for reproducing weather phenomena, like particle-based rain techniques, are presented in @cite_2 . The authors describe in details those methods to render, in a real-time system, very complex atmospheric physical phenomena such as strong rainfall, falling raindrops dripping off objects' surfaces, various reflections in surface materials and puddles, water ripples and puddles on the streets and so on.
@cite_2
2119535410
The visual effects of rain are complex. Rain consists of spatially distributed drops falling at high velocities. Each drop refracts and reflects the environment, producing sharp intensity changes in an image. A group of such falling drops creates a complex time varying signal in images and videos. In addition, due to the finite exposure time of the camera, intensities due to rain are motion blurred and hence depend on the background intensities. Thus, the visual manifestations of rain are a combination of both the dynamics of rain and the photometry of the environment. In this paper, we present the first comprehensive analysis of the visual effects of rain on an imaging system. We develop a correlation model that captures the dynamics of rain and a physics-based motion blur model that explains the photometry of rain. Based on these models, we develop efficient algorithms for detecting and removing rain from videos. The effectiveness of our algorithms is demonstrated using experiments on videos of complex scenes with moving objects and time-varying textures. The techniques described in this paper can be used in a wide range of applications including video surveillance, vision based navigation, video movie editing and video indexing retrieval.