scholarly journals Multi-sensor Formation Targets Template Matching Tracking Algorithm

2016 ◽  
Author(s):  
Haipeng Wang ◽  
Shuyi Jia ◽  
Ziling Wang
Keyword(s):  
Template Matching ◽  
Tracking Algorithm

An Anti- Occlusion Tracking Algorithm Based on MCD Correlation Matching

2013 ◽  
Vol 718-720 ◽  
pp. 2005-2010
Author(s):  
Pu Liu ◽  
Chun Ping Wang ◽  
Qiang Fu
Keyword(s):  
Target Tracking ◽  
Template Matching ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Template Method ◽  
Target Movement ◽  
Movement Prediction ◽  
Tracking Algorithms ◽  
The Stability ◽  
Correlation Matching

In order to improve the stability of target tracking under occlusion conditions，on the basis of researching some target tracking algorithms, this paper presents an algorithm based on MCD correlation matching, which combines multi sub-templates matching and target movement prediction. Besides, for occlusion characteristics, corresponding template matching criterions and updating methods are put forward. Experimental results show that, comparing with the single template method which updating frame by frame, the proposed algorithm has a certain anti-occlusion ability with better stability and continuity of target tracking under occlusion conditions.

Adjustable Tracking Algorithm with Adaptive Template Matching

2013 ◽  
Vol 11 (1) ◽  
pp. 34-39 ◽  
Author(s):  
Maria Curetti ◽  
Santiago Garcia Bravo ◽  
Gabriela S. Arri ◽  
Ladislao Mathe
Keyword(s):  
Template Matching ◽  
Tracking Algorithm

scholarly journals Non-Contact Measurement of the Surface Displacement of a Slope Based on a Smart Binocular Vision System

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2890 ◽  
Author(s):  
Leping He ◽  
Jie Tan ◽  
Qijun Hu ◽  
Songsheng He ◽  
Qijie Cai ◽  
...  
Keyword(s):  
Monitoring System ◽  
Template Matching ◽  
High Speed ◽  
Surface Deformation ◽  
Least Squares Method ◽  
Vision System ◽  
Deformation Monitoring ◽  
Tracking Algorithm ◽  
Zernike Moment ◽  
Tracking Accuracy

The paper presents an intelligent real-time slope surface deformation monitoring system based on binocular stereo-vision. To adapt the system to field slope monitoring, a design scheme of concentric marking point is proposed. Techniques including Zernike moment edge extraction, the least squares method, and k-means clustering are used to design a sub-pixel precision localization method for marker images. This study is mostly focused on the tracking accuracy of objects in multi-frame images obtained from a binocular camera. For this purpose, the Upsampled Cross Correlation (UCC) sub-pixel template matching technique is employed to improve the spatial-temporal contextual (STC) target-tracking algorithm. As a result, the tracking accuracy is improved to the sub-pixel level while keeping the STC tracking algorithm at high speed. The performance of the proposed vision monitoring system has been well verified through laboratory tests.

scholarly journals Visual Tracking via Feature Tensor Multimanifold Discriminate Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
Ting-quan Deng ◽  
Jia-shu Dai ◽  
Tian-zhen Dong ◽  
Ke-jia Yi
Keyword(s):  
Visual Tracking ◽  
Template Matching ◽  
Visual Surveillance ◽  
Tracking Algorithm ◽  
Multiple Objects ◽  
Discriminate Analysis ◽  
Neighborhood Relationship ◽  
Object Appearance ◽  
Gradient Based ◽  
Projection Matrices

In the visual tracking scenarios, if there are multiple objects, due to the interference of similar objects, tracking may fail in the progress of occlusion to separation. To address this problem, this paper proposed a visual tracking algorithm with discrimination through multimanifold learning. Color-gradient-based feature tensor was used to describe object appearance for accommodation of partial occlusion. A prior multimanifold tensor dataset is established through the template matching tracking algorithm. For the purpose of discrimination, tensor distance was defined to determine the intramanifold and intermanifold neighborhood relationship in multimanifold space. Then multimanifold discriminate analysis was employed to construct multilinear projection matrices of submanifolds. Finally, object states were obtained by combining with sequence inference. Meanwhile, the multimanifold dataset and manifold learning embedded projection should be updated online. Experiments were conducted on two real visual surveillance sequences to evaluate the proposed algorithm with three state-of-the-art tracking methods qualitatively and quantitatively. Experimental results show that the proposed algorithm can achieve effective and robust effect in multi-similar-object mutual occlusion scenarios.

An adaptive template matching-based single object tracking algorithm with parallel acceleration

2019 ◽  
Vol 64 ◽  
pp. 102603 ◽  
Author(s):  
Baicheng Yan ◽  
Limin Xiao ◽  
Hang Zhang ◽  
Daliang Xu ◽  
Li Ruan ◽  
...  
Keyword(s):  
Object Tracking ◽  
Template Matching ◽  
Tracking Algorithm ◽  
Single Object ◽  
Parallel Acceleration

scholarly journals Development of a Margin Determination Framework for Tumor-Tracking Radiation Therapy With Intraoperatively Implanted Fiducial Markers

2021 ◽  
Vol 11 ◽  
Author(s):  
Jihun Kim ◽  
Min Cheol Han ◽  
Jee Suk Chang ◽  
Chae-Seon Hong ◽  
Kyung Hwan Kim ◽  
...  
Keyword(s):  
Template Matching ◽  
Lung Metastases ◽  
Target Volume ◽  
Tracking Algorithm ◽  
Stereotactic Ablative Radiotherapy ◽  
Fiducial Markers ◽  
Internal Target Volume ◽  
Tumor Tracking ◽  
Decision Supporting ◽  
Optimal Set

PurposeTo develop an internal target volume (ITV) margin determination framework (or decision-supporting framework) for treating multiple lung metastases using CyberKnife Synchrony with intraoperatively implanted fiducial markers (IIFMs). The feasibility of using non-ideally implanted fiducial markers (a limited number and/or far from a target) for tracking-based lung stereotactic ablative radiotherapy (SABR) was investigated.MethodsIn the developed margin determination framework, an optimal set of IIFMs was determined to minimize a tracking uncertainty-specific ITV (ITVtracking) margin (margin required to cover target-to-marker motion discrepancy), i.e., minimize the motion discrepancies between gross tumor volume (GTV) and the selected set of fiducial markers (FMs). The developed margin determination framework was evaluated in 17 patients with lung metastases. To automatically calculate the respiratory motions of the FMs, a template matching-based FM tracking algorithm was developed, and GTV motion was manually measured. Furthermore, during-treatment motions of the selected FMs were analyzed using log files and compared with those calculated using 4D CTs.ResultsFor 41 of 42 lesions in 17 patients (97.6%), an optimal set of the IIFMs was successfully determined, requiring an ITVtracking margin less than 5 mm. The template matching-based FM tracking algorithm calculated the FM motions with a sub-millimeter accuracy compared with the manual measurements. The patient respiratory motions during treatment were, on average, significantly smaller than those measured at simulation for the patient cohort considered.ConclusionUse of the developed margin determination framework employing CyberKnife Synchrony with a limited number of IIFMs is feasible for lung SABR.

Object tracking algorithm based on the multispectral template matching

2018 ◽  
Author(s):  
Pavel V. Babayan ◽  
Sergey A. Smirnov ◽  
Valery V. Strotov ◽  
Vadim S. Muraviev ◽  
Maksim D. Ershov
Keyword(s):  
Object Tracking ◽  
Template Matching ◽  
Tracking Algorithm
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