A general line tracking algorithm based on computer vision

2016 ◽  
Author(s):  
Huanhuan Yang ◽  
Yinqiu Wang ◽  
Li Gao
Keyword(s):  
Computer Vision ◽  
Tracking Algorithm ◽  
General Line ◽  
Line Tracking

A real-time multi-cue hand tracking algorithm based on computer vision

2010 ◽  
Author(s):  
Zhigeng Pan ◽  
Yang Li ◽  
Mingmin Zhang ◽  
Chao Sun ◽  
Kangde Guo ◽  
...  
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Tracking Algorithm ◽  
Hand Tracking

scholarly journals An Efficient and Robust Multi-Object Recognition and Tracking Algorithm using Mask Region based Convolution Neural Network (R-CNN)

2019 ◽  
Vol 8 (9) ◽  
pp. 607-613
Keyword(s):  
Neural Network ◽  
Computer Vision ◽  
Object Recognition ◽  
Object Tracking ◽  
Ground Truth ◽  
Benchmark Dataset ◽  
Tracking Algorithm ◽  
Multiple Objects ◽  
High Quality ◽  
Extensive Simulation

Presently, Multi-Object tracking (MOT) is mainly applied for predicting the positions of many predefined objects across many successive frames with the provided ground truth position of the target in the first frame. The area of MOT gains more interest in the area of computer vision because of its applicability in various fields. Many works have been presented in recent years that intended to design a MOT algorithm with maximum accuracy and robustness. In this paper, we introduce an efficient as well as robust MOT algorithm using Mask R-CNN. The usage of Mask R-CNN effectively identifies the objects present in the image while concurrently creating a high-quality segmentation mask for every instance. The presented MOT algorithm is validated using three benchmark dataset and the results are extensive simulation. The presented tracking algorithm shows its efficiency to track multiple objects precisely

An Improved PID Control for Wheeled Line-Tracking Robot

2013 ◽  
Vol 401-403 ◽  
pp. 1661-1665
Author(s):  
Jun Chen ◽  
Jun Qiang
Keyword(s):  
Intelligent Control ◽  
Pid Control ◽  
Tracking Algorithm ◽  
New Method ◽  
Experimental Result ◽  
Channel Bend ◽  
Straight Line ◽  
Line Tracking ◽  
Design Requirements

This paper takes the wheeled line-tracking robot as the investigative object and the realization of intelligent control as the target, bases on SCM STC12C5A60S2, make the design of line-tracking robots soft hardware, and the line-tracking algorithm emphasis, presents a new method in PID control, and combining straight-line acceleration and channel bend modification, The experimental result shows that this line-tracking robot meets the design requirements with rapid moving and stability.

Multi-Object Tracking with Single Camera

2015 ◽  
Vol 740 ◽  
pp. 668-671
Author(s):  
Yu Bing Dong ◽  
Ying Sun ◽  
Ming Jing Li
Keyword(s):  
Computer Vision ◽  
Object Tracking ◽  
Block Matching ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Single Camera ◽  
Trajectory Prediction ◽  
Tracking Method

Multi-object tracking has been a challenging topic in computer vision. A Simple and efficient moving multi-object tracking algorithm is proposed. A new tracking method combined with trajectory prediction and a sub-block matching is used to handle the objects occlusion. The experimental results show that the proposed algorithm has good performance.

An extended line tracking algorithm

2013 ◽  
Author(s):  
Leonardo Romero Munoz ◽  
Moises Garcia Villanueva ◽  
Carlos Alberto Lara Alvarez
Keyword(s):  
Tracking Algorithm ◽  
Line Tracking

A Multi-Object Tracking Algorithm Based on Multi-Camera

2011 ◽  
Vol 135-136 ◽  
pp. 70-75
Author(s):  
Ming Xin Jiang ◽  
Hong Yu Wang ◽  
Chao Lin
Keyword(s):  
Computer Vision ◽  
Object Tracking ◽  
Real Time ◽  
Tracking Algorithm ◽  
Location Information ◽  
Multiple Cameras ◽  
Multiple Objects ◽  
Vanishing Points ◽  
Basic Aspect ◽  
Real Time Tracking

As a basic aspect of computer vision, reliable tracking of multiple objects is still an open and challenging issue for both theory studies and real applications. A novel multi-object tracking algorithm based on multiple cameras is proposed in this paper. We obtain the foreground likelihood maps in each view by modeling the background using the codebook algorithm. The view-to-view homographies are computed using several landmarks on the chosen plane. Then, we achieve the location information of multi-target at chest layer and realize the tracking task. The proposed algorithm does not require detecting the vanishing points of cameras, which reduces the complexity and improves the accuracy of the algorithm. The experimental results show that our method is robust to the occlusion and could satisfy the real-time tracking requirement.

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