Foreground-Background Segmentation Based on Codebook and Edge Detector

10/23/2014
by   Mikaël A. Mousse, et al.
0

Background modeling techniques are used for moving object detection in video. Many algorithms exist in the field of object detection with different purposes. In this paper, we propose an improvement of moving object detection based on codebook segmentation. We associate the original codebook algorithm with an edge detection algorithm. Our goal is to prove the efficiency of using an edge detection algorithm with a background modeling algorithm. Throughout our study, we compared the quality of the moving object detection when codebook segmentation algorithm is associated with some standard edge detectors. In each case, we use frame-based metrics for the evaluation of the detection. The different results are presented and analyzed.

READ FULL TEXT

page 3

page 4

research
05/11/2017

An Efficient Approach for Object Detection and Tracking of Objects in a Video with Variable Background

This paper proposes a novel approach to create an automated visual surve...
research
10/04/2015

Background Image Generation Using Boolean Operations

Tracking moving objects from a video sequence requires segmentation of t...
research
02/03/2014

A Robust Framework for Moving-Object Detection and Vehicular Traffic Density Estimation

Intelligent machines require basic information such as moving-object det...
research
09/04/2013

Boosting in Location Space

The goal of object detection is to find objects in an image. An object d...
research
09/27/2022

Critical Evaluation of LOCO dataset with Machine Learning

Purpose: Object detection is rapidly evolving through machine learning t...
research
09/05/2011

Moving Object Detection by Detecting Contiguous Outliers in the Low-Rank Representation

Object detection is a fundamental step for automated video analysis in m...

Please sign up or login with your details

Forgot password? Click here to reset