Low-complexity tracking-aware H.264 video compression for transportation surveillance

Eren Soyak*, Sotirios A. Tsaftaris, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalArticle

19 Scopus citations

Abstract

In centralized transportation surveillance systems, video is captured and compressed at low processing power remote nodes and transmitted to a central location for processing. Such compression can reduce the accuracy of centrally run automated object tracking algorithms. In typical systems, the majority of communications bandwidth is spent on encoding temporal pixel variations such as acquisition noise or local changes to lighting. We propose a tracking-aware, H.264-compliant compression algorithm that removes temporal components of low tracking interest and optimizes the quantization of frequency coefficients, particularly those that most influence trackers, significantly reducing bitrate while maintaining comparable tracking accuracy. We utilize tracking accuracy as our compression criterion in lieu of mean squared error metrics. Our proposed system is designed with low processing power and memory requirements in mind, and as such can be deployed on remote nodes. Using H.264/AVC video coding and a commonly used state-of-the-art tracker we show that our algorithm allows for over 90% bitrate savings while maintaining comparable tracking accuracy.

Original languageEnglish (US)
Article number5971775
Pages (from-to)1378-1389
Number of pages12
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume21
Issue number10
DOIs
StatePublished - Oct 1 2011

Keywords

  • Quantization
  • urban transportation video
  • video compression
  • video object tracking
  • video processing

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering

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