Maximizing the Use of Computational Resources in Multi-Camera Feedback Control
(2004) Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium p.360-367- Abstract
- In vision-based feedback control systems, the time to obtain sensor information is usually non-negligible, and these systems thereby possess fundamentally different timing behavior compared to standard real-time control applications. For many image-based tracking algorithms, however, it is possible to trade-off the computational time versus the accuracy of the produced position/orientation estimates.This paper presents a method for optimizing the use of computational resources in a multi-camera based positioning system. A simplified equation for the covariance of the position estimation error is calculated, which depends on the set of cameras used and the number of edge detection points in each image. An efficient algorithm for selection... (More)
- In vision-based feedback control systems, the time to obtain sensor information is usually non-negligible, and these systems thereby possess fundamentally different timing behavior compared to standard real-time control applications. For many image-based tracking algorithms, however, it is possible to trade-off the computational time versus the accuracy of the produced position/orientation estimates.This paper presents a method for optimizing the use of computational resources in a multi-camera based positioning system. A simplified equation for the covariance of the position estimation error is calculated, which depends on the set of cameras used and the number of edge detection points in each image. An efficient algorithm for selection of a suitable subset of the available cameras is presented, which attempts to minimize the estimation covariance given a desired, pre-specified maximum input-output latency of the feedback control loop.Simulations have been performed that capture the real-time properties of the vision-based tracking algorithm and the effects of the timing on the performance of the control system. The suggested strategy has been compared with heuristic algorithms, and it obtains large improvements in estimation accuracy and performance for objects both in free motion and under closed-loop position control. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/535971
- author
- Henriksson, Dan LU and Olsson, Tomas LU
- organization
- publishing date
- 2004
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- closed-loop position control, heuristic algorithms, estimation covariance, edge detection points, multicamera feedback control, sensor information, real-time control applications, computational resources, position estimation error, multicamera based positioning system, image-based tracking algorithms, vision-based feedback control systems
- host publication
- Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS04)
- pages
- 360 - 367
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium
- conference location
- Toronto, Ont., Canada
- conference dates
- 2004-05-25 - 2004-05-28
- external identifiers
-
- wos:000222239400040
- scopus:7744245329
- ISSN
- 1080-1812
- ISBN
- 0-7695-2148-7
- DOI
- 10.1109/RTTAS.2004.1317282
- language
- English
- LU publication?
- yes
- id
- 33f2b0d0-e314-4063-8008-72a50b00762e (old id 535971)
- date added to LUP
- 2016-04-01 16:12:53
- date last changed
- 2022-01-28 18:06:47
@inproceedings{33f2b0d0-e314-4063-8008-72a50b00762e,
abstract = {{In vision-based feedback control systems, the time to obtain sensor information is usually non-negligible, and these systems thereby possess fundamentally different timing behavior compared to standard real-time control applications. For many image-based tracking algorithms, however, it is possible to trade-off the computational time versus the accuracy of the produced position/orientation estimates.This paper presents a method for optimizing the use of computational resources in a multi-camera based positioning system. A simplified equation for the covariance of the position estimation error is calculated, which depends on the set of cameras used and the number of edge detection points in each image. An efficient algorithm for selection of a suitable subset of the available cameras is presented, which attempts to minimize the estimation covariance given a desired, pre-specified maximum input-output latency of the feedback control loop.Simulations have been performed that capture the real-time properties of the vision-based tracking algorithm and the effects of the timing on the performance of the control system. The suggested strategy has been compared with heuristic algorithms, and it obtains large improvements in estimation accuracy and performance for objects both in free motion and under closed-loop position control.}},
author = {{Henriksson, Dan and Olsson, Tomas}},
booktitle = {{Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS04)}},
isbn = {{0-7695-2148-7}},
issn = {{1080-1812}},
keywords = {{closed-loop position control; heuristic algorithms; estimation covariance; edge detection points; multicamera feedback control; sensor information; real-time control applications; computational resources; position estimation error; multicamera based positioning system; image-based tracking algorithms; vision-based feedback control systems}},
language = {{eng}},
pages = {{360--367}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Maximizing the Use of Computational Resources in Multi-Camera Feedback Control}},
url = {{https://lup.lub.lu.se/search/files/4604636/625604.pdf}},
doi = {{10.1109/RTTAS.2004.1317282}},
year = {{2004}},
}