Video synopsis is a technique that condenses a long surveillance video to a short summary. It faces challenges to process objects originally occluding each other in the source video. Previous approaches either treat occlusion objects as a single object, which however reduce compression ratio; or have to separate occlusion objects individually, but destroy interactions between them and yield visual artifacts. This paper presents a novel data structure called Flexible Object Graph (FOG) to handle original occlusions. Our FOG-based video synopsis approach can manipulate each object flexibly while preserving the original occlusions between them, achieving high synopsis ratio while maintaining interactions of objects. A challenging issue that comes with the introduction of FOG is that FOG may contain circulations that yield conflicts. We solve this problem by proposing a circulation conflict resolving algorithm. Furthermore, video synopsis methods usually minimize a multi-objective energy function. Previous approaches optimize the multiple objectives simultaneously which needs to strike a balance between them. Instead, we propose a stepwise optimization strategy consuming less running time while producing higher quality. Experiments demonstrate the effectiveness of our method.

视频概要是一种将较长的监控视频浓缩为简短摘要的技术。它面临着处理源视频中最初相互遮挡的对象的挑战。以前的方法要么将遮挡对象视为单个对象，但会降低压缩率;或者必须单独分离遮挡对象，但会破坏它们之间的交互并产生视觉伪影。本文提出了一种称为柔性对象图 （FOG） 的新型数据结构来处理原始遮挡。我们基于 FOG 的视频概要方法可以灵活地操作每个对象，同时保留它们之间的原始遮挡，在保持对象交互的同时实现高概要比率。引入 FOG 带来的一个具有挑战性的问题是 FOG 可能包含产生冲突的环流。我们通过提出一种流通冲突解决算法来解决这个问题。此外，视频概要方法通常会最小化多目标能量函数。以前的方法同时优化多个目标，这需要在它们之间取得平衡。相反，我们提出了一种逐步优化策略，消耗更少的运行时间，同时产生更高的质量。实验证明了我们方法的有效性。