DeepAI
Log In Sign Up

M4CD: A Robust Change Detection Method for Intelligent Visual Surveillance

02/14/2018
by   Kunfeng Wang, et al.
0

In this paper, we propose a robust change detection method for intelligent visual surveillance. This method, named M4CD, includes three major steps. Firstly, a sample-based background model that integrates color and texture cues is built and updated over time. Secondly, multiple heterogeneous features (including brightness variation, chromaticity variation, and texture variation) are extracted by comparing the input frame with the background model, and a multi-source learning strategy is designed to online estimate the probability distributions for both foreground and background. The three features are approximately conditionally independent, making multi-source learning feasible. Pixel-wise foreground posteriors are then estimated with Bayes rule. Finally, the Markov random field (MRF) optimization and heuristic post-processing techniques are used sequentially to improve accuracy. In particular, a two-layer MRF model is constructed to represent pixel-based and superpixel-based contextual constraints compactly. Experimental results on the CDnet dataset indicate that M4CD is robust under complex environments and ranks among the top methods.

READ FULL TEXT

page 5

page 6

page 7

page 9

page 10

page 11

page 13

09/04/2017

A Multilayer-Based Framework for Online Background Subtraction with Freely Moving Cameras

The exponentially increasing use of moving platforms for video capture i...
06/19/2014

MRF-based Background Initialisation for Improved Foreground Detection in Cluttered Surveillance Videos

Robust foreground object segmentation via background modelling is a diff...
11/28/2016

On the Role and the Importance of Features for Background Modeling and Foreground Detection

Background modeling has emerged as a popular foreground detection techni...
10/16/2018

A Robust Local Binary Similarity Pattern for Foreground Object Detection

Accurate and fast extraction of the foreground object is one of the most...
03/29/2020

Co-occurrence Background Model with Superpixels for Robust Background Initialization

Background initialization is an important step in many high-level applic...
04/27/2012

Background subtraction based on Local Shape

We present a novel approach to background subtraction that is based on t...
10/26/2021

A Horizon Detection Algorithm for Maritime Surveillance

The horizon line is a valuable feature in the maritime environment as it...