We present 2SDS (Scene Separation and Data Selection algorithm), a temporal segmentation algorithm used in real-time video stream interpretation. It complements CNN-based models to make use of temporal information in videos. 2SDS can detect the change between scenes in a video stream by com-paring the image difference between two frames. It separates a video into segments (scenes), and by combining itself with a CNN model, 2SDS can select the optimal result for each scene. In this paper, we will be discussing some basic methods and concepts behind 2SDS, as well as presenting some preliminary experiment results regarding 2SDS. During these experiments, 2SDS has achieved an overall accuracy of over 90%.

翻译：我们提出了2SDS（场景分离与数据选择算法），一种用于实时视频流解析的时间分割算法。该算法通过利用视频帧间的图像差异检测场景切换，从而补充基于CNN的模型以充分利用视频中的时序信息。2SDS能够将视频分割为若干片段（场景），并通过与CNN模型相结合，为每个场景选取最优结果。本文讨论了2SDS背后的基本方法与概念，并呈现了相关初步实验结果。实验表明，2SDS的整体准确率超过90%。