Performance analysis of real time object tracking system based on compressive sensing

2017 ◽  
Author(s):  
Urvi Anil Agrawal ◽  
Preetida Vinayakray Jani
Keyword(s):  
Performance Analysis ◽  
Compressive Sensing ◽  
Object Tracking ◽  
Real Time ◽  
Tracking System

A real-time visual object tracking system based on Kalman filter and MB-LBP feature matching

2014 ◽  
Vol 75 (4) ◽  
pp. 2393-2409 ◽  
Author(s):  
Zebin Cai ◽  
Zhenghui Gu ◽  
Zhu Liang Yu ◽  
Hao Liu ◽  
Ke Zhang
Keyword(s):  
Kalman Filter ◽  
Object Tracking ◽  
Real Time ◽  
Feature Matching ◽  
Tracking System ◽  
Visual Object ◽  
Visual Object Tracking

scholarly journals Real-time object tracking system based on field-programmable gate array and convolution neural network

2016 ◽  
Vol 14 (1) ◽  
pp. 172988141668270 ◽  
Author(s):  
Congyi Lyu ◽  
Haoyao Chen ◽  
Xin Jiang ◽  
Peng Li ◽  
Yunhui Liu
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Object Tracking ◽  
Real Time ◽  
Field Programmable Gate Array ◽  
Tracking System ◽  
Convolution Neural Network ◽  
Processing Unit ◽  
Field Programmable ◽  
Gate Array

Vision-based object tracking has lots of applications in robotics, like surveillance, navigation, motion capturing, and so on. However, the existing object tracking systems still suffer from the challenging problem of high computation consumption in the image processing algorithms. The problem can prevent current systems from being used in many robotic applications which have limitations of payload and power, for example, micro air vehicles. In these applications, the central processing unit- or graphics processing unit-based computers are not good choices due to the high weight and power consumption. To address the problem, this article proposed a real-time object tracking system based on field-programmable gate array, convolution neural network, and visual servo technology. The time-consuming image processing algorithms, such as distortion correction, color space convertor, and Sobel edge, Harris corner features detector, and convolution neural network were redesigned using the programmable gates in field-programmable gate array. Based on the field-programmable gate array-based image processing, an image-based visual servo controller was designed to drive a two degree of freedom manipulator to track the target in real time. Finally, experiments on the proposed system were performed to illustrate the effectiveness of the real-time object tracking system.

Real-Time Object Tracking System on FPGAs

2011 ◽  
Author(s):  
Su Liu ◽  
Alexandros Papakonstantinou ◽  
Hongjun Wang ◽  
Deming Chen
Keyword(s):  
Object Tracking ◽  
Real Time ◽  
Tracking System

scholarly journals Validation of a Video-Based Performance Analysis System (Mediacoach®) to Analyze the Physical Demands during Matches in LaLiga

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4113 ◽  
Author(s):  
Jose Luis Felipe ◽  
Jorge Garcia-Unanue ◽  
David Viejo-Romero ◽  
Archit Navandar ◽  
Javier Sánchez-Sánchez
Keyword(s):  
Performance Analysis ◽  
Real Time ◽  
Tracking System ◽  
Maximum Speed ◽  
Camera Tracking ◽  
Total Distance ◽  
Maximum Bias ◽  
The Difference ◽  
Analysis System ◽  
Gps System

The aim of the present study was to assess the accuracy of a multi-camera tracking system (Mediacoach®) to track elite football players’ movements in real time. A total of 207 observations of 38 official matches from Liga 1, 2, 3™ (2nd Spanish Division, season 2017/18) were included in the study (88 defenders, 84 midfielders, and 35 attackers of the same team). Total distance (TD, m) distance in zone 4 (DZ4) at a speed of 14–21 km/h, distance in zone 5 (DZ5) at a speed of 21–24 km/h (DZ5), distance in zone 6 (DZ6) at a speed of ≥24 km/h, maximum speed (km/h), and number of sprints (actions above 24 km/h) were registered with the Apex® GPS system (STATSports™, Newry, N. Ireland) and Mediacoach® semi-automatic tracking system (LaLiga™, Madrid, Spain). The level of agreement between variables estimated by the two systems was analyzed. Bias was also calculated by deducting the GPS estimated value from the video estimated value, and then dividing the difference score by the GPS estimated value. All variables showed high ICC values (>0.75) and very large correlations (r > 0.70). However the video-based performance analysis system overestimated the results obtained in the different speed zones (DZ5: +16.59 ± 62.29 m; LOA95%: −105.49 to 138.68; DZ6: +93.26 ± 67.76 m; LOA95%: −39.55 to 226.07), the number of sprints (+2.27 ± 2.94; LOA95%: −3.49 to 8.02), and the maximum speed (+0.32 ± 1.25 km/h; LOA95%: −2.13 to 2.77). The maximum bias was found in DZ6 (47%). This demonstrates that Mediacoach® is as accurate as a GPS system to obtain objective data in real time, adapted to physical and movement demands of elite football, especially for total distance and distances traveled at medium speeds.

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