Space moving target detection and tracking method in complex background

Maritime moving target detection and tracking through particle filter based track-before-detect (PF-TBD) has significant practical value for airborne forward-looking scanning radar. However, villainous weather and surging of ocean waves make it extremely difficult to accurately obtain a statistical model for sea clutter. As the likelihood ratio calculation in PF-TBD is dependent on the distribution of the clutter, the performance of traditional distribution-based PF-TBD seriously declines. To resolve these difficulties, this paper proposes a new target detection and tracking method, named spectral-residual-binary-entropy-based PF-TBD (SRBE-PF-TBD), which is independent from the prior knowledge of sea clutter. In the proposed method, the likelihood ratio calculation is implemented by first extracting the spectral residual of the input image to obtain the saliency map, and then constructing likelihood ratio through a binarization processing and information entropy calculation. Simulation results show that the proposed method had superior performance of maritime moving target detection and tracking.

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Dim small moving target detection and tracking method based on spatial-temporal joint processing model

Infrared Physics & Technology ◽

10.1016/j.infrared.2019.102973 ◽

2019 ◽

Vol 102 ◽

pp. 102973

Author(s):

Ping-yue Lv ◽

Chang-qing Lin ◽

Sheng-li Sun

Keyword(s):

Target Detection ◽

Moving Target ◽

Moving Target Detection ◽

Joint Processing ◽

Tracking Method ◽

Detection And Tracking

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Study of Multi Target Tracking Algorithm Based on CRF Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.556-562.3860 ◽

2014 ◽

Vol 556-562 ◽

pp. 3860-3863

Author(s):

Chang Hui Wang

Keyword(s):

Target Detection ◽

Video Tracking ◽

Future Research ◽

Moving Target ◽

Complex Scene ◽

Moving Target Detection ◽

Optical Flow Method ◽

Detection And Tracking ◽

Complex Background ◽

Multi Target Tracking

Moving target detection and tracking in complex background is the key technology in the field of computer vision, which has become one of the focus researches for many scholars at home and abroad. Many applications, such as robot navigation, video tracking, are closely related with the moving object detection and tracking in complex background. In this paper, we improve the traditional stochastic model and target matching algorithm, combining with the feature optical flow method, to detect and track moving target detection in complex scene, and get online modified CRF model. It provides theoretical support and guidance technology for future research.

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The Research of Moving Target Detection and Tracking System Based on DM6437

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.734.203 ◽

2015 ◽

Vol 734 ◽

pp. 203-206

Author(s):

En Zeng Dong ◽

Sheng Xu Yan ◽

Kui Xiang Wei

Keyword(s):

Target Detection ◽

Digital Signal Processor ◽

Moving Objects ◽

Tracking System ◽

Digital Signal ◽

Gaussian Mixture ◽

Background Model ◽

Moving Target ◽

Moving Target Detection ◽

Detection And Tracking

In order to enhance the rapidity and the accuracy of moving target detection and tracking, and improve the speed of the algorithm on the DSP (digital signal processor), an active visual tracking system was designed based on the gaussian mixture background model and Meanshift algorithm on DM6437. The system use the VLIB library developed by TI, and through the method of gaussian mixture background model to detect the moving objects and use the Meanshift tracking algorithm based on color features to track the target in RGB space. Finally, the system is tested on the hardware platform, and the system is verified to be quickness and accuracy.

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