Real-time multi-camera video analytics system on GPU

Güler P., Emeksiz D., Temizel A., Teke M., Temizel T.

JOURNAL OF REAL-TIME IMAGE PROCESSING, vol.11, no.3, pp.457-472, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 3
  • Publication Date: 2016
  • Doi Number: 10.1007/s11554-013-0337-2
  • Journal Name: JOURNAL OF REAL-TIME IMAGE PROCESSING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.457-472
  • Keywords: Video surveillance, Video analytics, Real-time, CUDA, GPU
  • Middle East Technical University Affiliated: Yes

Abstract

In this article, parallel implementation of a real-time intelligent video surveillance system on Graphics Processing Unit (GPU) is described. The system is based on background subtraction and composed of motion detection, camera sabotage detection (moved camera, out-of-focus camera and covered camera detection), abandoned object detection, and object-tracking algorithms. As the algorithms have different characteristics, their GPU implementations have different speed-up rates. Test results show that when all the algorithms run concurrently, parallelization in GPU makes the system up to 21.88 times faster than the central processing unit counterpart, enabling real-time analysis of higher number of cameras.