Abstract: A congestion prediction device, a congestion prediction method, and a storage medium are provided. A mapping outputs an output variable when input variables are input to the mapping. The output variable indicates a degree of congestion in a predetermined specific area. The mapping is learned in advance by machine learning. The input variables include congestion variables. Each of the congestion variables indicates a degree of congestion in the specific area at regular time intervals within a specific period. The output variable indicates a degree of congestion after a lapse of the regular time interval from an end time of the specific period.

Abstract: An exemplary image processing system first writes normal line information and color information into the G buffer and depth information into the depth buffer for a first object. Next, at a time of writing the normal line information into the G buffer for a second object, the exemplary image processing system calculates a difference between the depth information of a first object and the depth information of the second object, and blends the normal line information of the first object with the normal line information of the second object based on the difference, and writes the blended normal line information into the G buffer. The exemplary image processing system then renders an image in a frame buffer based on information stored in the G buffer and light source information.