scholarly journals Multi-Target Tracking Using Windowed Fourier Single-Pixel Imaging

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7934
Author(s):  
Jinyu Zhang ◽  
Taiyang Hu ◽  
Xiaolang Shao ◽  
Mengxuan Xiao ◽  
Yingjiao Rong ◽  
...  
Keyword(s):  
Target Tracking ◽  
Joint Estimation ◽  
Frame Rate ◽  
Moving Targets ◽  
Tracking Method ◽  
Close Proximity ◽  
Multi Target Tracking ◽  
Video Experiment ◽  
First Time ◽  
Single Pixel

The single-pixel imaging (SPI) technique enables the tracking of moving targets at a high frame rate. However, when extended to the problem of multi-target tracking, there is no effective solution using SPI yet. Thus, a multi-target tracking method using windowed Fourier single-pixel imaging (WFSI) is proposed in this paper. The WFSI technique uses a series of windowed Fourier basis patterns to illuminate the target. This method can estimate the displacements of K independently moving targets by implementing 6K measurements and calculating 2K windowed Fourier coefficients, which is a measurement method with low redundancy. To enhance the capability of the proposed method, we propose a joint estimation approach for multi-target displacement, which solves the problem where different targets in close proximity cannot be distinguished. Using the independent and joint estimation approaches, multi-target tracking can be implemented with WFSI. The accuracy of the proposed multi-target tracking method is verified by numerical simulation to be less than 2 pixels. The tracking effectiveness is analyzed by a video experiment. This method provides, for the first time, an effective idea of multi-target tracking using SPI.

Vision tracking based on adaptive interactive fusion

2020 ◽  
Vol 39 (6) ◽  
pp. 9037-9044
Author(s):  
Junyan Shi ◽  
Han Jiang
Keyword(s):  
Target Tracking ◽  
Personnel Management ◽  
Template Matching ◽  
Feature Fusion ◽  
Research Work ◽  
Feature Representation ◽  
Moving Target ◽  
Moving Targets ◽  
Tracking Method ◽  
Complex Scenes

Under the influence of COVID-19, detection and identification of moving targets are very important for personnel management. A lot of research work has improved the accuracy and robustness of the moving target tracking method, but the recognition accuracy of the traditional target tracking method in complex scenes (lighting changes, background interference, posture changes and other factors) is not satisfactory. In this paper, in view of the limitations of single feature representation of target objects, the method of fusion of HSV color features and edge direction features is used to identify and detect moving targets. In each frame of the tracking process, the weight of each feature is adjusted adaptively according to the proposed fusion strategy, and the position of the target is located by using the method of double template matching. Experiments show that the proposed tracking algorithm based on multi feature fusion can meet the requirements of moving target recognition in complex scenes. The method proposed in this paper has a certain reference value for personnel management under the influence of COVID-19.

An Improved Method of Tracking the Motion of Sperm Target

2012 ◽  
Vol 241-244 ◽  
pp. 2940-2943
Author(s):  
Zhen Rong Deng ◽  
Wen Ming Huang ◽  
Dong Yu ◽  
Yin Wei Li
Keyword(s):  
Target Tracking ◽  
Nearest Neighbor ◽  
Data Association ◽  
Improved Method ◽  
Tracking Accuracy ◽  
Processing Methods ◽  
Tracking Method ◽  
Multi Target Tracking

This paper analyzes the multi-target tracking of sperm by using the improved nearest neighbor data association tracking method which predicts the position where the sperm may appear in the next frame by computing the interframe-distance and direction of the sperm. Also, in order to dealing with the situation of tracking lose and many-to-one tracking, we proposed two processing methods for sperm re-tracking of tracking lost compensation and tracking forecast minimum-range. The experiment shows this algorithm has better tracking accuracy and higher efficiency.

scholarly journals Multi-Target Tracking Using a Vision Chip and its Applications to Real-Time Visual Measurement

2005 ◽  
Vol 17 (2) ◽  
pp. 121-129 ◽  
Author(s):  
Yoshihiro Watanabe ◽  
◽  
Takashi Komuro ◽  
Shingo Kagami ◽  
Masatoshi Ishikawa
Keyword(s):  
Image Processing ◽  
Target Tracking ◽  
Real Time ◽  
High Speed ◽  
Vision System ◽  
Visual Observation ◽  
Frame Rate ◽  
Vision Chip ◽  
Visual Measurement ◽  
Multi Target Tracking

Real-time image processing at high frame rates could play an important role in various visual measurement. Such image processing can be realized by using a high-speed vision system imaging at high frame rates and having appropriate algorithms processed at high speed. We introduce a vision chip for high-speed vision and propose a multi-target tracking algorithm for the vision chip utilizing the unique features. We describe two visual measurement applications, target counting and rotation measurement. Both measurements enable excellent measurement precision and high flexibility because of high-frame-rate visual observation achievable. Experimental results show the advantages of vision chips compared with conventional visual systems.

Efficient Multi-Target Tracking Method Based on Fusion Morphology Filtering in Traffic Video Detection

2011 ◽  
Vol 179-180 ◽  
pp. 1412-1416
Author(s):  
Wei Bin Chen ◽  
Zhi Yang Gu ◽  
Xin Zhang
Keyword(s):  
Target Tracking ◽  
Mean Shift ◽  
Tracking Method ◽  
Mean Shift Algorithm ◽  
Video Frames ◽  
Analysis Technique ◽  
Multi Target Tracking ◽  
Morphological Operator ◽  
Real Video ◽  
Morphology Filter

Aiming at the tracking real-time and accuracy problem of traffic videos, a efficient Multi-target tracking method based on Fusion morphology filter is proposed. The proposed Multi-target tracking method used by Morphologically Fused Tracking approach and combined with pyramid mean shift algorithm, quantizes the deterioration effects encountered on marble surfaces by providing the number, location and shape of deterioration spots. First the detection based on the application of morphological operator sequential filters by reconstruction with structuring elements of growing size. Then adopt a traditional tracking method such as adaptive pyramid mean shift, because it uses the pyramid analysis technique and can determine the pyramid level adaptively to decrease the number of iterations required to achieve region. We validate our approach on tracking examples using real video sequences, it can precisely partition and track the predetermined objects in video frames.

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