Real-Time Tracking of Multiple Objects Using Fiducials for Augmented Reality

2001 ◽  
Vol 7 (6) ◽  
pp. 495-506 ◽  
Author(s):  
Jose Molineros ◽  
Rajeev Sharma
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Multiple Objects ◽  
Real Time Tracking

Robust Real-Time Tracking of Multiple Objects by Volumetric Mass Densities

2013 ◽  
Author(s):  
Horst Possegger ◽  
Sabine Sternig ◽  
Thomas Mauthner ◽  
Peter M. Roth ◽  
Horst Bischof
Keyword(s):  
Real Time ◽  
Multiple Objects ◽  
Real Time Tracking

scholarly journals An integrated augmented reality surgical navigation platform using multi-modality imaging for guidance

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250558
Author(s):  
Harley H. L. Chan ◽  
Stephan K. Haerle ◽  
Michael J. Daly ◽  
Jinzi Zheng ◽  
Lauren Philp ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Navigation System ◽  
Surgical Navigation ◽  
Multimodality Imaging ◽  
Anatomical Structures ◽  
Image Guided ◽  
Surgical Navigation System ◽  
Virtual Images ◽  
Real Time Tracking

An integrated augmented reality (AR) surgical navigation system that potentially improves intra-operative visualization of concealed anatomical structures. Integration of real-time tracking technology with a laser pico-projector allows the surgical surface to be augmented by projecting virtual images of lesions and critical structures created by multimodality imaging. We aim to quantitatively and qualitatively evaluate the performance of a prototype interactive AR surgical navigation system through a series of pre-clinical studies. Four pre-clinical animal studies using xenograft mouse models were conducted to investigate system performance. A combination of CT, PET, SPECT, and MRI images were used to augment the mouse body during image-guided procedures to assess feasibility. A phantom with machined features was employed to quantitatively estimate the system accuracy. All the image-guided procedures were successfully performed. The tracked pico-projector correctly and reliably depicted virtual images on the animal body, highlighting the location of tumour and anatomical structures. The phantom study demonstrates the system was accurate to 0.55 ± 0.33mm. This paper presents a prototype real-time tracking AR surgical navigation system that improves visualization of underlying critical structures by overlaying virtual images onto the surgical site. This proof-of-concept pre-clinical study demonstrated both the clinical applicability and high precision of the system which was noted to be accurate to <1mm.

scholarly journals A Robust Algorithm for Real Time Tracking With Optical Flow

2019 ◽  
Vol 9 (1) ◽  
pp. 887-892
Keyword(s):  
Optical Flow ◽  
Object Tracking ◽  
Real Time ◽  
Traffic Monitoring ◽  
Moving Object ◽  
Computational Time ◽  
Multiple Objects ◽  
Flow Information ◽  
Data Processor ◽  
Real Time Tracking

Object tracking is a troublesome undertaking and significant extent in data processor perception and image handling community. Some of the applications are protection surveillance, traffic monitoring on roads, offense detection and medical imaging. In this paper a recent technique for tracking of moving object is intended. Optical flow information authorizes us to know the displacement and speed of objects personate in a scene. Apply optical flow to the image gives flow vectors of the points to distinguishing the moving aspects. Optical flow is accomplished by Lucas canade algorithm. This algorithm is superior to other algorithms. The outcomes reveals that the intend algorithm is efficient and accurate object tracking method. This paper depicts a smoothing algorithm to track the moving object of both single and multiple objects in real time. The main issue of high computational time is greatly reduced in this proposed work

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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