9. The video annotation method of claim 6 , wherein said performing said predicting stage further comprises: inputting at least one third shot antecedent to said second shot in said second scene, and respectively selecting at least one third critical frame of said at least one third shot; respectively extracting low-level features of said second critical frame and low-level features of said at least one third critical frame, thereby obtaining a plurality of second feature vectors; performing said grouping step on said second feature vectors in accordance with a statistic distance algorithm, and corresponding said second feature vectors to said identification codes respectively; finding frequent patterns of said shot groups in said second scene in accordance with the continuous relevance algorithm, thereby obtaining a plurality of second sequential rules, wherein said second sequential rules are the sequential transaction combinations of any two identification codes arbitrarily selected in said second scene; and inputting said second sequential rules into said sequential model, thereby obtaining said keyword sequential probability list used for indicating the respective appearing probabilities of said fundamental words corresponding to said second sequential rules with respect to said second feature vectors.
9. The video annotation method of claim 6 , wherein said performing said predicting stage further comprises: inputting at least one third shot antecedent to said second shot in said second scene, and respectively selecting at least one third critical frame of said at least one third shot; respectively extracting low-level features of said second critical frame and low-level features of said at least one third critical frame, thereby obtaining a plurality of second feature vectors; performing said grouping step on said second feature vectors in accordance with a statistic distance algorithm, and corresponding said second feature vectors to said identification codes respectively; finding frequent patterns of said shot groups in said second scene in accordance with the continuous relevance algorithm, thereby obtaining a plurality of second sequential rules, wherein said second sequential rules are the sequential transaction combinations of any two identification codes arbitrarily selected in said second scene; and inputting said second sequential rules into said sequential model, thereby obtaining said keyword sequential probability list used for indicating the respective appearing probabilities of said fundamental words corresponding to said second sequential rules with respect to said second feature vectors. 11. The video annotation method of claim 9 , wherein the low-level features of said second critical frame and the low-level features of said at least one third critical frame are selected from the group consisting of a shape descriptor, a scalable color descriptor, a homogeneous texture descriptor and any combinations thereof.