This paper introduces the design and implementation of a semantic concept based video retrieval system

which consists of shot boundary detection and key frame extraction subsystem

semantic concept detection subsystem and user retrieval subsystem. First

digital video is divided into hierarchical structure for retrieval. Then

efficient low level feature of key frames are extracted. Support Vector Machine is used to detect concepts in such key frames

and the video retrieval is based on those concepts. In the procedure of concept detection

we take a linearly weighted fusion method based on validation precision to improve the average precision. Experiments show that the Mean Average Precision of our system is as high as the best one of all submissions.