Low-Cost Approach for Improving Video Transmission Efficiency in WVSN

doi:10.1007/s12204-020-2202-3

Abstract

Abstract: The wireless visual sensor network (WVSN) as a new emerged intelligent visual system, has been
applied in many video monitoring sites. However, there is still great challenge because of the limited wireless
network bandwidth. To resolve the problem, we propose a real-time dynamic texture approach which can detect
and reduce the temporal redundancy during many successive image frames. Firstly, an adaptively learning background
model is improved to discover successive similar image frames from the inputting video sequence. Then,
the dynamic texture model based on the singular value decomposition is adopted to distinguish foreground and
background element dynamics. Furthermore, a background discarding strategy based on visual motion coherence
is proposed to determine whether each image frame is streamed or not. To evaluate the trade-off performance
of the proposed method, it is tested on the CDW-2014 dataset, which can accurately detect the first foreground
frame when the moving objects of interest appear in the field of view in the most tested dynamic scenes, and
the misdetection rate of the undetected foreground frames is near to zero. Compared to the original stream, it
can reduce the occupied bandwidth a lot and its computational cost is relatively lower than the state-of-the-art
methods.

Key words: wireless visual sensor network (WVSN)| temporal redundancy| foreground| background| dynamic
texture

摘要： The wireless visual sensor network (WVSN) as a new emerged intelligent visual system, has been
applied in many video monitoring sites. However, there is still great challenge because of the limited wireless
network bandwidth. To resolve the problem, we propose a real-time dynamic texture approach which can detect
and reduce the temporal redundancy during many successive image frames. Firstly, an adaptively learning background
model is improved to discover successive similar image frames from the inputting video sequence. Then,
the dynamic texture model based on the singular value decomposition is adopted to distinguish foreground and
background element dynamics. Furthermore, a background discarding strategy based on visual motion coherence
is proposed to determine whether each image frame is streamed or not. To evaluate the trade-off performance
of the proposed method, it is tested on the CDW-2014 dataset, which can accurately detect the first foreground
frame when the moving objects of interest appear in the field of view in the most tested dynamic scenes, and
the misdetection rate of the undetected foreground frames is near to zero. Compared to the original stream, it
can reduce the occupied bandwidth a lot and its computational cost is relatively lower than the state-of-the-art
methods.

关键词: wireless visual sensor network (WVSN)| temporal redundancy| foreground| background| dynamic
texture

CLC Number:

TP 391.4

LIU Min, DENG Bin, TANG Ying, WU Minghu, WANG Juan . Low-Cost Approach for Improving Video Transmission Efficiency in WVSN[J]. Journal of Shanghai Jiao Tong University(Science), 2020, 25(5): 600-605.

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