Video abstraction is a process to pick up some important shots on a video, while the important shots might vary on the persons subjectivity. Previous works on video abstraction use only one low level feature to choose an important shot. This thesis proposes an abstraction scheme that selects a set of shots which simultaneously satisfies the desired features(or objective functions) of a good abstraction. Since the complexity of the computation to find a set of shots which maximizes the sum of object function values is $0({2^n})$, the proposed .scheme uses a simulated annealing based searching method to find the suboptimal value within a short period of time. Upon the experimental results on various videos, we could argue that the proposed abstraction scheme could produce a reasonable video abstraction. The proposed abstraction scheme used to build a digital video library.