Improving Video Segmentation by Fusing Depth Cues and the Visual Background Extractor (ViBe) Algorithm

Sensors
Xiaoqin ZhouChenguang Yang

Abstract

Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in three-dimensional space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D (Red-Green-Blue and Depth) algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.

References

Dec 30, 2010·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Olivier Barnich, Marc Van Droogenbroeck
Dec 14, 2011·IEEE Transactions on Pattern Analysis and Machine Intelligence·Z KalalJiri Matas
Jun 29, 2013·IEEE Transactions on Cybernetics·Jungong HanJamie Shotton
Jul 17, 2013·Sensors·Enrique J Fernandez-SanchezEduardo Ros

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Citations

Feb 20, 2019·Sensors·Maryamsadat RasoulidaneshShahram Payandeh

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Methods Mentioned

BETA
feature extraction

Software Mentioned

OpenCV SDK2
ViBe1D
ViBe
DEVB
DECB
MOG4D
OpenNI1

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