Traffic surveillance video coding with libraries of vehicles and background

Abstract

This paper presents a video coding scheme tailored for traffic surveillance videos, which features a pre-built library that is utilized in both encoder and decoder to pursue higher compression efficiency. We are motivated by the observation that, in traffic surveillance videos, not only the background is steady for a long while, but also the foreground (e.g. vehicles) contains high redundancy. For example, in the video taken by a traffic monitoring camera, we can observe that the passing-through vehicles are usually similar. However, the redundancy in the vehicles and the background is not fully exploited in the current video coding schemes. To address this problem, we propose a library-based video coding scheme. Specifically, for each static monitoring camera, we can collect video in a period, and build a library of vehicles and background from that video. When encoding the following video of that camera, we utilize the pre-built library by searching similar vehicles and background from the library and using the retrieved vehicles and background to help encode. Accordingly, the decoder also refers to the same library to reconstruct the video. We design efficient algorithms for building the library, searching in the library, as well as utilizing the library for encoding/decoding, to fulfill the proposed scheme. Our scheme is implemented upon the state-of-the-art video coding system–High Efficiency Video Coding (HEVC), and is tested on our own collected traffic surveillance videos. Experimental results show that, compared to the HEVC anchor, our proposed scheme achieves as high as 47.0%, 37.1%, and 34.8% BD-rate reduction, under random-access, low-delay B, and low-delay P settings, respectively. Our scheme also achieves higher compression efficiency than the existing background-based methods for surveillance video coding.