WisenetMD: Motion Detection Using Dynamic Background Region Analysis

TL;DR

This paper introduces WisenetMD, a motion detection method that analyzes dynamic background regions to reduce false positives caused by environmental movements, improving accuracy in surveillance video analysis.

Contribution

The paper presents a novel dynamic background region analysis technique that effectively reduces false positives in motion detection for surveillance cameras.

Findings

Reduces false positives from wind and flowing water.

Achieves competitive processing speed compared to existing algorithms.

Validated on CDnet 2012/2014 datasets.

Abstract

Motion detection algorithms that can be applied to surveillance cameras such as CCTV (Closed Circuit Television) have been studied extensively. Motion detection algorithm is mostly based on background subtraction. One main issue in this technique is that false positives of dynamic backgrounds such as wind shaking trees and flowing rivers might occur. In this paper, we proposed a method to search for dynamic background region by analyzing the video and removing false positives by re-checking false positives. The proposed method was evaluated based on CDnet 2012/2014 dataset obtained at "changedetection.net" site. We also compared its processing speed with other algorithms.