Abstract: In order to address the challenge associated with the analysis and visualization of large datasets, a method and apparatus provides for visualizing data clouds using color and opacity blending. The information stored within the data cloud is represented using a data container object. The colors and opacities associated with the container object's data point or points is blended to develop two-dimensional computer generated imagery that is unique to the virtual reference point chosen, typically within an OpenGL environment. The result is the ability to understand the sample density of large interactively rendered datasets from different reference points and as the datasets change over time.

Abstract: In order to address the challenge associated with the analysis and visualization of large datasets, a method and apparatus provides for visualizing data clouds using color and opacity blending. The information stored within the data cloud is represented using a data container object. The colors and opacities associated with the container object's data point or points is blended to develop two-dimensional computer generated imagery that is unique to the virtual reference point chosen, typically within an OpenGL environment. The result is the ability to understand the sample density of large interactively rendered datasets from different reference points and as the datasets change over time.