Accelerated hardware video object segmentation: From foreground detection to connected components labelling

APPIAH, Kofi, HUNTER, Andrew, DICKINSON, Patrick and MENG, Hongying (2010). Accelerated hardware video object segmentation: From foreground detection to connected components labelling. Computer Vision and Image Understanding, 114 (11), 1282-1291.

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Abstract

This paper demonstrates the use of a single-chip FPGA for the segmentation of moving objects in a video sequence. The system maintains highly accurate background models, and integrates the detection of foreground pixels with the labelling of objects using a connected components algorithm. The background models are based on 24-bit RGB values and 8-bit gray scale intensity values. A multimodal background differencing algorithm is presented, using a single FPGA chip and four blocks of RAM. The real-time connected component labelling algorithm, also designed for FPGA implementation, run-length encodes the output of the background subtraction, and performs connected component analysis on this representation. The run-length encoding, together with other parts of the algorithm, is performed in parallel; sequential operations are minimized as the number of run-lengths are typically less than the number of pixels. The two algorithms are pipelined together for maximum efficiency.

Item Type:	Article
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018:	Faculty of Science, Technology and Arts > Department of Computing
Identification Number:	https://doi.org/10.1016/j.cviu.2010.03.021
Page Range:	1282-1291
Depositing User:	Kofi Appiah
Date Deposited:	22 Aug 2018 14:03
Last Modified:	18 Mar 2021 11:00
URI:	https://shura.shu.ac.uk/id/eprint/22195

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