The Society of Convergence Knowledge Transactions ISSN:2287-8920(Print) 융복합지식학회논문지

In this paper, we propose a memory management strategy for large-scale video editing in memory-constrained environments. When implementing large-scale video editing functions, loading all video data into memory for processing can lead to a shortage of memory capacity, and an efficient memory management strategy is needed to solve this problem. Hence, this paper suggests a method that does not manage all video data in memory, but instead only references the location information of each frame, and loads data into memory only when actual data is needed for editing or playback, thus reducing memory usage. An effective class structure for this is also proposed. When the process of editing large-scale videos in a video editing program implemented with the structure proposed in this paper was analyzed using a performance profiler, it was confirmed that editing could be done with a very small amount of memory compared to the size of the original video.