We present improved algorithms for cut, fade, and dissolve detection which are fundamental steps in digital video analysis. In particular, we propose a new adaptive threshold determination method that is shown to reduce artifacts created by noise and motion in scene cut detection. We also describe new two-step algorithms for fade and dissolve detection, and introduce a method for eliminating false positives from a list of detected candidate transitions. In our detailed study of these gradual shot transitions, our objective has been to accurately classify the type of transitions (fade-in, fade-out, and dissolve) and to precisely locate the boundary of the transitions. This distinguishes our work from other early work in scene change detection which tends to focus primarily on identifying the existence of a transition rather than its precise temporal extent. We evaluate our improved algorithms against two other commonly used shot detection techniques on a comprehensive data set, and demonstrate the improved performance due to our enhancements.
我们提出了用于剪切,淡入淡出和溶解检测的改进算法,这些算法是数字视频分析的基本步骤。特别是,我们提出了一种新的自适应阈值确定方法,该方法可减少场景切换检测中由噪声和运动产生的伪像。我们还描述了用于淡入淡出和溶解检测的新的两步算法,并介绍了一种从检测到的候选过渡列表中消除误报的方法。在我们对这些渐变镜头过渡的详细研究中,我们的目标是准确地对过渡类型进行分类(淡入,淡出和溶解)并精确定位过渡的边界。这使我们的工作与场景变更检测中的其他早期工作区分开来,后者通常主要专注于识别过渡的存在而不是其精确的时间范围。在全面的数据集上,我们针对其他两种常用的镜头检测技术对改进的算法进行了评估,并展示了由于我们的增强而带来的改进性能。 P>
机译:使用支持向量机同时检测视频中的突然剪切和溶解
机译:基于信息论的镜头切换/淡入淡出检测和视频摘要
机译:用于视频分割的鲁棒多特征切割检测算法
机译:视频分割中剪切,淡入和溶解检测过程的新增强功能
机译:显着削减:一种基于显着能量最小化的视频对象自动分割方法
机译:使用中智图切分割算法进行甲状腺弹性成像视频的合格渲染图像选择
机译:视频分割中剪切,淡入淡出和溶解检测过程的新增强功能