Occlusion-Preserved Surveillance Video Synopsis with Flexible Object Graph

Abstract

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.