Moving Target Tracking Using Sparse Optical Flow Method

2013 ◽  
Vol 718-720 ◽  
pp. 2335-2339
Author(s):  
Tian Ding Chen ◽  
Jian Hu ◽  
Chao Lu ◽  
Zhong Jiao He
Keyword(s):  
Optical Flow ◽  
Target Tracking ◽  
New Method ◽  
Moving Target ◽  
Tracking Accuracy ◽  
Experimental Conditions ◽  
Moving Target Tracking ◽  
Research Production ◽  
Harris Corner ◽  
Comparison Results

Moving target tracking is a hot research spot of computer vision and applied in various fields. In this paper, a new tracking method base on sparse optical flow is put forward. In this method, targets are tracked through calculating the movements of Harris corner points, rather than the movements of all pixel points. Experiments results show that the tracking effect of this new method is pretty good. Tracking accuracy can reach more than 80% in most experimental conditions. And according to other peoples research production, experiments based on dense optical flow are done to compare with the new method proposed in this paper. The comparison results show that the new method has high calculation efficiency. This indicates that the method has feasibility and practical value.

Efficient Moving Target Tracking Algorithm: Design and Implementation of the Sand-Table Tracking Algorithm

2013 ◽  
Vol 475-476 ◽  
pp. 1032-1039
Author(s):  
Jia Qi Li
Keyword(s):  
Target Tracking ◽  
Algorithm Design ◽  
Tracking Algorithm ◽  
Moving Target ◽  
Tracking Accuracy ◽  
Moving Target Tracking ◽  
Design And Implementation ◽  
Tracking Ability

Working on the design of a new algorithm :sand_table algorithm.The algorithm could work well in recognizing and tracking an single moving target shot by camera or in a video .The algorithm works simple with low operation cost.May used in tracking different object of many kinds.The algorithm imitate the the process of falling sands to Greatly enhance the tracking ability and tracking accuracy.

scholarly journals Research on Moving Target Tracking Based on FDRIG Optical Flow

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1122
Author(s):  
Gong ◽  
Wang
Keyword(s):  
Optical Flow ◽  
Target Tracking ◽  
Research Work ◽  
Flow Equation ◽  
Superior Performance ◽  
Moving Target ◽  
Moving Target Tracking ◽  
Motion Sequence ◽  
Tracking Model ◽  
Vehicle Motion

Aiming at the problem of moving target recognition, a moving target tracking model based on FDRIG optical flow is proposed. First, the optical flow equation was analyzed from the theory of optical flow. Then, with the energy functional minimization, the FDRIG optical flow technique was proposed. Taking a road section of a university campus as an experimental section, 30 vehicle motion sequence images were considered as objects to form a vehicle motion sequence image with a complex background. The proposed FDRIG optical flow was used to calculate the vehicle motion optical flow field by the Halcon software. Comparable with the classic Horn and Schunck (HS) and Lucas and Kande (LK) optical flow algorithm, the monitoring results proved that the FDRIG optical flow was highly precise and fast when tracking a moving target. The Ettlinger Tor traffic scene was then taken as the second experimental object; FDRIG optical flow was used to analyze vehicle motion. The superior performance of the FDRIG optical flow was further verified. The whole research work shows that FDRIG optical flow has good performance and speed in tracking moving targets and can be used to monitor complex target motion information in real-time.

Research on Underwater Target Tracking Based on Contour Detection

2011 ◽  
Vol 317-319 ◽  
pp. 890-896
Author(s):  
Ming Jun Zhang ◽  
Yuan Yuan Wan ◽  
Zhen Zhong Chu
Keyword(s):  
Prediction Model ◽  
Target Tracking ◽  
Tracking System ◽  
Contour Detection ◽  
Motion Prediction ◽  
Moving Target ◽  
Contour Extraction ◽  
Tracking Accuracy ◽  
Tracking Method ◽  
Underwater Target

The traditional centroid tracking method over-relies on the accuracy of segment, which easily lead to loss of underwater moving target. This paper presents an object tracking method based on circular contour extraction, combining region feature and contour feature. Through the correction to circle features, the problem of multiple solutions causing by Hough transform circle detection is avoided. A new motion prediction model is constructed to make up the deficiency that three-order motion prediction model has disadvantage of high dimension and large calculation. The predicted position of object centroid is updated and corrected by circle contour, forming prediction-measurement-updating closed-loop target tracking system. To reduce system processing time, on the premise of the tracking accuracy, a dynamic detection method based on target state prediction model is proposed. The results of contour extraction and underwater moving target experiments demonstrate the effectiveness of the proposed method.

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