Authors:
Wenjun Zhou
1
;
Shun’ichi Kaneko
1
;
Manabu Hashimoto
2
;
Yutaka Satoh
3
and
Dong Liang
4
Affiliations:
1
Hokkaido University, Japan
;
2
Chukyo University, Japan
;
3
National Institute of Advanced Industrial Science and Technology (AIST), Japan
;
4
Nanjing University of Aeronautics and Astronautics, China
Keyword(s):
Background Model, Co-occurrence Pixel-Block Pairs (CPB), Object Detection, Correlation Depended Decision Function, Severe Scenes, Hypothesis on Degradation (HoD).
Abstract:
This paper presents a prospective background model for robust object detection in severe scenes. This background
model using a novel algorithm, Co-occurrence Pixel-block Pairs (CPB), that extracts the spatiotemporal
information of pixels from background and identifies the state of pixels at current frame. First, CPB
realizes a robust background model for each pixel with spatiotemporal information based on a “pixel to block”
structure. And then, CPB employs an efficient evaluation strategy to detect foreground sensitively, which is
named as correlation dependent decision function. On the basis of this, a Hypothesis on Degradation Modification
(HoD) for CPB is introduced to adapt dynamic changes in scenes and reinforce robustness of CPB to
against “noise” in real conditions. This proposed model is robust to extract foreground against changes, such
as illumination changes and background motion. Experimental results in different challenging datasets prove
that our model has good
effect for object detection.
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