Abstract： In view of sensitivity of initial samples division and easy fall into local optimum in existing unsupervised clustering methods of video key-frame extraction without considering temporal order of shot content, a novel ordered samples clustering algorithm was proposed based on artificial immune. According to traditional artificial immune based clustering algorithm, memory recognition mechanism for antigens was introduced, and clone and hyper mutation mechanism for antibodies was improved. A video key -frame extraction method of artificial immune based on ordered samples clustering was proposed. The image frame sequence in a shot was regarded as an antigen sequence invading the body. Based on the mechanisms of primary response and second response, the memory cell pools for each antigen were obtained. The continuous antigens recognized by the same memory cell pool was formed a cluster, and the frame nearest to the cluster center was extracted as a key-frame. The experiments on various videos were completed. The results show that the proposed method has high fidelity and compression ratio, and the key-frames reflecting real shots contents can be extracted effectively.
詹永照, 汪满容, 柯佳. 基于人工免疫有序聚类的视频关键帧提取方法[J]. 江苏大学学报（自然科学版）, 2012, 33(2): 199-204.
ZHAN Yong zhao, WANG Man rong, KE Jia. Video keyframe extraction using ordered samples clustering based on artificial immune[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2012, 33(2): 199-204.
2012, Vol. 33 
