Moving Target Detection Method Research Articles

Infrared small moving target detection method based on graph matching

We apply graph matching method to detect infrared small moving targets using image sequences. Candidates (interest points) detected in the first frame form one graph and the same candidates in the last frame form another one. The real moving targets are extracted by matching these two graphs. Experimental results demonstrate that the proposed method is robust and efficient to the translation and rotation of the background.

Moving object detection based on background image set and sparse analysis

This paper proposed a moving target detection method based on the background image set and sparse representation.The method combined the Robust Principal Component Analysis(RPCA) and the image block analysis method based on sparse representation.The authors got a series of background images from a video sequence by RPCA,and combined these background images as the background image set,treating image block as basic unit,and moving target was extracted from input frame by image block analysis method based on sparse representation.The simulation results indicate that when the background illumination mutates,the proposed method can effectively eliminate the impact of environment noise and reduce the false detection rate of target detection.

Moving object detection in aerial video based on spatiotemporal saliency

In this paper, the problem of moving object detection in aerial video is addressed. While motion cues have been extensively exploited in the literature, how to use spatial information is still an open problem. To deal with this issue, we propose a novel hierarchical moving target detection method based on spatiotemporal saliency. Temporal saliency is used to get a coarse segmentation, and spatial saliency is extracted to obtain the object’s appearance details in candidate motion regions. Finally, by combining temporal and spatial saliency information, we can get refined detection results. Additionally, in order to give a full description of the object distribution, spatial saliency is detected in both pixel and region levels based on local contrast. Experiments conducted on the VIVID dataset show that the proposed method is efficient and accurate.

Moving target detection method based on pixel clustering

Moving target detection method based on pixel clustering

A Nonlinear Constrained Optimization Method of MTD

This paper presents a nonlinear constrained optimization of the moving target detection (MTD) filter design method, which can be better designed to detect moving targets need to control the filter characteristics of the main-lobe and side-lobes, but also has less parameter constraints. Simulation results show that the MTD filters designed with a better clutter suppression performance and real-time engineering applications.

基于时频分析的成像小弱运动目标检测方法

基于时频分析的成像小弱运动目标检测方法

A quick moving target detection method based on real-time airborne videos

In this paper, a fast detection method of moving target from real-time airborne videos is presented. We first explore the motion relationship in an airborne video and utilise the global motion estimation to estimate the background movement, and then use binocular interpolation for motion compensation; thus, the moving target detection in dynamic airborne videos is converted into detection in static backgrounds. A method involving the multiplication of the differences of the symmetrical images among three adjacent frames is adopted to enhance moving target and increase the difference between the target and background noises. The regional growth and morphological image processing techniques are employed finally to realise target segmentation. Experimental results demonstrate the effectiveness and robustness of our algorithm.