1. A computer-implemented method, comprising: on a video content analysis device: delineating video data into intention units; extracting features from the video data, wherein each feature is used to estimate one or more human intentions wherein the extracting features includes extracting attention-specific features, and wherein each attention-specific feature represents one dimension of human attention, and wherein the extracting attention-specific features includes analyzing four dimensions of attention (DoA): an attention stability, an attention energy, an attention window, and a camera pattern; classifying the intention units into intention categories; and selecting a number of categories to be the intention categories and defining each of the intention categories according to a type of video content characteristic of one of the human intentions, wherein the intention categories include a static scene category, a dynamic event category, a close-un view category, a beautiful scenery category, a switch record category, a longtime record category, and a just record category.