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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 692921, 6 pages
Research Article

A TBB-CUDA Implementation for Background Removal in a Video-Based Fire Detection System

School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China

Received 7 December 2013; Revised 30 January 2014; Accepted 30 January 2014; Published 3 March 2014

Academic Editor: Massimo Scalia

Copyright © 2014 Fan Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a parallel TBB-CUDA implementation for the acceleration of single-Gaussian distribution model, which is effective for background removal in the video-based fire detection system. In this framework, TBB mainly deals with initializing work of the estimated Gaussian model running on CPU, and CUDA performs background removal and adaption of the model running on GPU. This implementation can exploit the combined computation power of TBB-CUDA, which can be applied to the real-time environment. Over 220 video sequences are utilized in the experiments. The experimental results illustrate that TBB+CUDA can achieve a higher speedup than both TBB and CUDA. The proposed framework can effectively overcome the disadvantages of limited memory bandwidth and few execution units of CPU, and it reduces data transfer latency and memory latency between CPU and GPU.