Position Estimation Based Object Tracking across Multiple Cameras

2007 ◽  
Author(s):  
Yingna Deng ◽  
Hong Zhu ◽  
Gang Li ◽  
and Ruirui Ji
Keyword(s):  
Object Tracking ◽  
Position Estimation ◽  
Multiple Cameras

Object tracking in the presence of occlusions using multiple cameras

2013 ◽  
Vol 9 (2) ◽  
pp. 1-36 ◽  
Author(s):  
Ali O. Ercan ◽  
Abbas El Gamal ◽  
Leonidas J. Guibas
Keyword(s):  
Object Tracking ◽  
Multiple Cameras

scholarly journals 3D Contact Position Estimation of Image-Based Areal Soft Tactile Sensor with Printed Array Markers and Image Sensors

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3796
Author(s):  
Jong-il Lee ◽  
Suwoong Lee ◽  
Hyun-Min Oh ◽  
Bo Ram Cho ◽  
Kap-Ho Seo ◽  
...  
Keyword(s):  
Tactile Sensor ◽  
Estimation Algorithm ◽  
Industrial Applications ◽  
Position Estimation ◽  
Image Sensors ◽  
Multiple Cameras ◽  
Tactile Sensors ◽  
Input Devices ◽  
The Stability ◽  
Contact Position

Tactile sensors have been widely used and researched in various fields of medical and industrial applications. Gradually, they will be used as new input devices and contact sensors for interactive robots. If a tactile sensor is to be applied to various forms of human–machine interactions, it needs to be soft to ensure comfort and safety, and it should be easily customizable and inexpensive. The purpose of this study is to estimate 3D contact position of a novel image-based areal soft tactile sensor (IASTS) using printed array markers and multiple cameras. First, we introduce the hardware structure of the prototype IASTS, which consists of a soft material with printed array markers and multiple cameras with LEDs. Second, an estimation algorithm for the contact position is proposed based on the image processing of the array markers and their Gaussian fittings. A series of basic experiments was conducted and their results were analyzed to verify the effectiveness of the proposed IASTS hardware and its estimation software. To ensure the stability of the estimated contact positions a Kalman filter was developed. Finally, it was shown that the contact positions on the IASTS were estimated with a reasonable error value for soft haptic applications.

scholarly journals Real Time Object Tracking Method using Multiple Cameras

2012 ◽  
Vol 17 (4) ◽  
pp. 51-59 ◽  
Author(s):  
In-Tae Jang ◽  
Dong-Woo Kim ◽  
Young-Jun Song ◽  
Hyeok-Bong Kwon ◽  
Jae-Hyeong Ahn
Keyword(s):  
Object Tracking ◽  
Real Time ◽  
Multiple Cameras ◽  
Tracking Method

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.

scholarly journals Control of a Movable Robot Head Using Vision-Based Object Tracking

2019 ◽  
Vol 9 (4) ◽  
pp. 2503
Author(s):  
Moh Khairudin ◽  
G.D. Chen ◽  
M.C. Wu ◽  
R. Asnawi ◽  
Nurkhamid Nurkhamid
Keyword(s):  
Object Tracking ◽  
Tracking System ◽  
High Accuracy ◽  
Object Identification ◽  
Position Estimation ◽  
Object Position ◽  
Rgb Images ◽  
Robot Head ◽  
Object Marking ◽  
The Right

<span lang="EN-US">This paper presents a visual tracking system to support the movement of the robot head for detecting the existence of objects. Object identification and object position estimation were conducted using image-based processing. The movement of the robot head was in four directions namely  to the right, left, top, and bottom of the robot head. Based on the distance of the object, it shifted the object to many points to </span><span lang="IN">assess</span><span lang="EN-US"> the accuracy of the process of tracking the object. The targeted objects are detected through several processes, namely normalization of RGB images, thresholding, and object marking. The process of tracking the object conducted by the robot head varied in 40 various object points with high accuracy. The further the object’s distance to the robot, the smaller the corner of the movement of the robot produced compared to the movement of the robot head to track an object that was closer even though with the same distance stimulant shift object. However, for the distance and the shift of the same object, the level of accuracy showed almost the same results. The results showed the movement of the robot head to track the object under the head of the robot produced the movement with a larger angular error compared to the movement of the robot head in another direction even though with the stimulant distance of the same object position and the distance shift of the same object.</span>

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