A novel metadata extraction method for surveillance video

Abstract

Surveillance videos are increasing massively with monitoring cameras widely deployed in cities. Metadata of moving objects in videos can reduce video storage and be utilized in many video analysis applications. The whole metadata extraction is too time-consuming to be fulfilled quickly. Therefore, it is urgent to parallelize and accelerate the extraction process. However, iterative execution of traditional metadata extraction methods makes the parallelization quite challenging. In this paper, we propose a novel Parallel Metadata Extraction (PME) method for surveillance video. A novel video segmentation algorithm is designed to segment whole video into independent video segments. The metadata of each video segment is extracted independently and simultaneously on computer nodes, which will be integrated later to guarantee the completeness of the metadata. Performance evaluations demonstrate that PME can accelerate extraction process greatly almost without metadata loss.