Moving Object Localization in Thermal Imagery by Forward-backward MHI

Authors:
Zhaozheng Yin;Robert Collins
Affiliations:
Pennsylvania State University, University Park, PA;Pennsylvania State University, University Park, PA
Venue:
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Year:
2006

Citing 0
Cited 4

An adaptive focus-of-attention model for video surveillance and monitoring

Machine Vision and Applications
Optical flow and principal component analysis-based motion detection in outdoor videos

EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Real-time multiple moving targets detection from airborne IR imagery by dynamic Gabor filter and dynamic Gaussian detector

Journal on Image and Video Processing
Multiframe Many---Many Point Correspondence for Vehicle Tracking in High Density Wide Area Aerial Videos

International Journal of Computer Vision

Quantified Score

Hi-index	0.00

Visualization

Abstract

Detecting moving objects automatically is a key component of an automatic visual surveillance and tracking system. In airborne thermal video, the moving objects may be small, color information is not available, and even intensity appearance may be camouflaged. Previous motionbased moving object detection approaches often use background subtraction, inter-frame difference or three-frame difference. In this paper, we describe a detection and localization method based on forward-backward motion history images (MHI). This method can accurately detect location and shape of moving objects for initializing a tracker. Using long and varied video sequences, we quantify the effectiveness of this method.