Depth Computation Using Optical Flow and Least Squares
Depth Computation Using Optical Flow and Least Squares
Depth computation in robotics is an important step towards providing robust and accurate navigation capabilities to a mobile robot. In this paper we examine the problem of depth estimation with the view to be used in parsimonious systems where fast and accurate measurements are critical. For this purpose we have combined two methods, namely optical flow and least squares in order to infer depth estimates between a robot and a landmark. In the optical flow method the variation of the optical flow vector at varying distances and velocities is observed. In the least squares method snapshots of a landmark are taken from different robot positions. The results of the two methods show that there is a significant increase in depth estimation accuracy by combining optical flow and least squares.
Diamantas, Sotirios
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Oikonomidis, Anastasios
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Crowder, Richard
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Diamantas, Sotirios
569b0bb8-9d90-447c-8a23-16d38f29444f
Oikonomidis, Anastasios
876dbe2e-cc0e-4620-a72b-2b44ccf32a07
Crowder, Richard
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Diamantas, Sotirios, Oikonomidis, Anastasios and Crowder, Richard
(2010)
Depth Computation Using Optical Flow and Least Squares.
2010 IEEE/SICE International Symposium on System Integration (SII 2010), Sendai, Japan.
21 - 22 Dec 2010.
(Submitted)
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Conference or Workshop Item
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Abstract
Depth computation in robotics is an important step towards providing robust and accurate navigation capabilities to a mobile robot. In this paper we examine the problem of depth estimation with the view to be used in parsimonious systems where fast and accurate measurements are critical. For this purpose we have combined two methods, namely optical flow and least squares in order to infer depth estimates between a robot and a landmark. In the optical flow method the variation of the optical flow vector at varying distances and velocities is observed. In the least squares method snapshots of a landmark are taken from different robot positions. The results of the two methods show that there is a significant increase in depth estimation accuracy by combining optical flow and least squares.
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Submitted date: 20 December 2010
Additional Information:
Event Dates: 21/22 December 2010
Venue - Dates:
2010 IEEE/SICE International Symposium on System Integration (SII 2010), Sendai, Japan, 2010-12-21 - 2010-12-22
Organisations:
Agents, Interactions & Complexity
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Local EPrints ID: 271771
URI: http://eprints.soton.ac.uk/id/eprint/271771
PURE UUID: 6f390ea3-ae82-41b4-8e9f-39e68eb6af8f
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Date deposited: 12 Dec 2010 13:26
Last modified: 14 Mar 2024 09:39
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Contributors
Author:
Sotirios Diamantas
Author:
Anastasios Oikonomidis
Author:
Richard Crowder
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