1. A method of providing a service for long-term understanding of background modeling, the method comprising providing: a gradient determiner that uses features extracted from input video data to determine dimensional gradient models for pixel image data of the input video and define average image pixel gradient models for each pixel of the pixel image data by averaging the determined gradients with previous gradients of the each pixel, and also with gradients of neighboring pixels as a function of their distance to the pixel; a background modeler that constructs and updates background pixel models for a static image scene of the input video data by using the averaged pixel gradient data that have similar orientation and magnitude for each of a plurality of pixel model sets, wherein each pixel model set is associated with a weight that determines if the each pixel model set represents background or non-background data; and a foreground estimator that uses the constructed and updated background models to estimate foreground areas in the static image scene of the input video data by comparing the averaged pixel gradients with corresponding ones of the background models, wherein a pixel is determined to be a foreground and not a background pixel in response to a distance from the averaged pixel gradient data to a corresponding background model pixel set equaling or exceeding a threshold distance value, or to the distance being less than the threshold but closer to another foreground model pixel set than to the corresponding background model pixel set.