Effectively compressing Near-Duplicate Videos in a joint way

With the increasing popularity of social network, more and more people tend to store and transmit information in visual format, such as image and video. However, the cost of this convenience brings about a shock to traditional video servers and expose them under the risk of overloading. Among the huge amount of online videos, there are quite a number of Near-Duplicate Videos (NDVs). Although many works have been proposed to detect NDVs, few researches are investigated to compress these NDVs in a more effective way than independent compression. In this work, we utilize the data redundancy of NDVs and propose a video coding method to jointly compress NDVs. In order to employ the proposed video coding method, a number of pre-processing functions are designed to explore the correlation of visual information among NDVs and to suit the video coding requirements. Experimental results verify that the proposed video coding method is able to effectively compress NDVs and thus save video data storage.