Abstract: Reverberation parameters for one or more positions of interest are derived from graphics data used for displaying a computer-generated environment. For each position of interest for which reverberation parameters are desired, environmental parameters including distances and the hardness of features in a range of interest and at points on cubemap faces are automatically determined from the graphics data. The environmental parameters are stored with the graphics data and associated with each position of interest. Upon rendering of the computer-generated environment, reverberation property set values usable by a reverberation engine are calculated or interpolated between predetermined values according to the environmental parameters.

Abstract: Reverberation parameters for one or more positions of interest are derived from graphics data used for displaying a computer-generated environment. For each position of interest for which reverberation parameters are desired, environmental parameters including distances and the hardness of features in a range of interest and at points on cubemap faces are automatically determined from the graphics data. The environmental parameters are stored with the graphics data and associated with each position of interest. Upon rendering of the computer-generated environment, reverberation property set values usable by a reverberation engine are calculated or interpolated between predetermined values according to the environmental parameters.

Abstract: Reverberation parameters for one or more positions of interest are derived from graphics data used for displaying a computer-generated environment. For each position of interest for which reverberation parameters are desired, environmental parameters including distances and the hardness of features in a range of interest and at points on cubemap faces are automatically determined from the graphics data. The environmental parameters are stored with the graphics data and associated with each position of interest. Upon rendering of the computer-generated environment, reverberation property set values usable by a reverberation engine are calculated or interpolated between predetermined values according to the environmental parameters.

Abstract: A learning controller overcomes tuning problems in vehicle simulation programs by estimating requisite vehicle-specific parameters, effectively learning from its mistakes, as the vehicle is automatically driven around a track. After a sufficient period of calibration, the learned parameters are automatically saved to a car-specific file. The file parameters may be loaded in the controller in the future to optimally control a vehicle without the need to re-run the learning procedure.

Abstract: A system and method for maintaining a background model of an image sequence by processing on multiple spatial scales. These multiple spatial scales include a pixel scale, a regional scale and a frame scale. The image sequence undergoes pixel processing that determines a current background model and provides an initial pixel assignment as either a background or a foreground pixel. Region processing further refines the initial pixel assignments by considering relationships between pixels and possibly reassigning pixels. Frame processing further refines the current background model by determining whether a substantial change has occurred in the actual background and, if so, providing a more accurate background model.

Abstract: Reverberation parameters for one or more positions of interest are derived from graphics data used for displaying a computer-generated environment. For each position of interest for which reverberation parameters are desired, environmental parameters including distances and the hardness of features in a range of interest and at points on cubemap faces are automatically determined from the graphics data. The environmental parameters are stored with the graphics data and associated with each position of interest. Upon rendering of the computer-generated environment, reverberation property set values usable by a reverberation engine are calculated or interpolated between predetermined values according to the environmental parameters.

Abstract: An image background maintenance system and method for maintaining a background model of an image sequence by processing on multiple spatial scales. These multiple spatial scales include a pixel scale, a regional scale and a frame scale. The image sequence undergoes pixel processing that determines a current background model and provides an initial pixel assignment as either a background or a foreground pixel. Region processing further refines the initial pixel assignments by considering relationships between pixels and possibly reassigning pixels. Frame processing further refines the current background model by determining whether a substantial change has occurred in the actual background and, if so, providing a more accurate background model.

Abstract: An image background maintenance system and method for maintaining a background model of an image sequence by processing on multiple spatial scales. These multiple spatial scales include a pixel scale, a regional scale and a frame scale. The image sequence undergoes pixel processing that determines a current background model and provides an initial pixel assignment as either a background or a foreground pixel. Region processing further refines the initial pixel assignments by considering relationships between pixels and possibly reassigning pixels. Frame processing further refines the current background model by determining whether a substantial change has occurred in the actual background and, if so, providing a more accurate background model.

Abstract: An image background maintenance system and method for maintaining a background model of an image sequence by processing on multiple spatial scales. These multiple spatial scales include a pixel scale, a regional scale and a frame scale. The image sequence undergoes pixel processing that determines a current background model and provides an initial pixel assignment as either a background or a foreground pixel. Region processing further refines the initial pixel assignments by considering relationships between pixels and possibly reassigning pixels. Frame processing further refines the current background model by determining whether a substantial change has occurred in the actual background and, if so, providing a more accurate background model.