1. An object identification method, comprising: dividing an input video into a number of video shots, each containing one or more video frames; detecting target-class object occurrences and related-class object occurrences in each video shot; generating hint information including a small subset of frames representing the input video; performing object tracking and recognition based on the hint information; combining tracking and recognition results; and outputting labeled objects based on the combined tracking and recognition results; wherein generating hint information including a small subset of frames representing the input video further includes: applying a video summarization approach; applying k-means clustering algorithms using identify-sensitive features on all detected objects; and performing initial object identification using a knowledge database; wherein the hint information possesses a desired identity coverage, a desired local representation, a desired pose variation coverage and a desired illumination variation coverage.