Free Space Computation From Stochastic Occupancy Grids Based On Iconic Kalman Filtered Disparity Maps

Carsten Høilund, Thomas B. Moeslund, Claus B. Madsen, Mohan M. Trivedi

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

3 Citationer (Scopus)

Resumé

This paper presents a method for determining the free space in a scene as viewed by a vehicle-mounted camera.
Using disparity maps from a stereo camera and known camera motion, the disparity maps are first filtered by an iconic Kalman filter, operating on each pixel individually, thereby reducing variance and increasing the density of the filtered disparity map. Then, a stochastic occupancy grid is calculated from the filtered disparity map, providing a top-down view of the scene where the uncertainty of disparity measurements are taken into account. These occupancy grids are segmented to indicate a maximum depth free of obstacles, enabling the marking of free space in the accompanying intensity image. The test shows successful marking of free space in the evaluated scenarios in addition to significant improvement in disparity map quality.
OriginalsprogEngelsk
TitelInternational Conference on Computer Vision Theory and Applications (VISAPP)
Antal sider4
Vol/bind1
ForlagInstitute for Systems and Technologies of Information, Control and Communication
Publikationsdato17 maj 2010
Sider164-167
ISBN (Elektronisk)978-989-674-028-3
StatusUdgivet - 17 maj 2010
BegivenhedThe International Conference on Computer Vision Theory and Applications - Angers, Frankrig
Varighed: 17 maj 201021 maj 2010

Konference

KonferenceThe International Conference on Computer Vision Theory and Applications
LandFrankrig
ByAngers
Periode17/05/201021/05/2010

Fingerprint

Cameras
Kalman filters
Pixels
Uncertainty

Citer dette

Høilund, C., Moeslund, T. B., Madsen, C. B., & Trivedi, M. M. (2010). Free Space Computation From Stochastic Occupancy Grids Based On Iconic Kalman Filtered Disparity Maps. I International Conference on Computer Vision Theory and Applications (VISAPP) (Bind 1, s. 164-167). Institute for Systems and Technologies of Information, Control and Communication.
Høilund, Carsten ; Moeslund, Thomas B. ; Madsen, Claus B. ; Trivedi, Mohan M. / Free Space Computation From Stochastic Occupancy Grids Based On Iconic Kalman Filtered Disparity Maps. International Conference on Computer Vision Theory and Applications (VISAPP). Bind 1 Institute for Systems and Technologies of Information, Control and Communication, 2010. s. 164-167
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title = "Free Space Computation From Stochastic Occupancy Grids Based On Iconic Kalman Filtered Disparity Maps",
abstract = "This paper presents a method for determining the free space in a scene as viewed by a vehicle-mounted camera.Using disparity maps from a stereo camera and known camera motion, the disparity maps are first filtered by an iconic Kalman filter, operating on each pixel individually, thereby reducing variance and increasing the density of the filtered disparity map. Then, a stochastic occupancy grid is calculated from the filtered disparity map, providing a top-down view of the scene where the uncertainty of disparity measurements are taken into account. These occupancy grids are segmented to indicate a maximum depth free of obstacles, enabling the marking of free space in the accompanying intensity image. The test shows successful marking of free space in the evaluated scenarios in addition to significant improvement in disparity map quality.",
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Høilund, C, Moeslund, TB, Madsen, CB & Trivedi, MM 2010, Free Space Computation From Stochastic Occupancy Grids Based On Iconic Kalman Filtered Disparity Maps. i International Conference on Computer Vision Theory and Applications (VISAPP). bind 1, Institute for Systems and Technologies of Information, Control and Communication, s. 164-167, The International Conference on Computer Vision Theory and Applications, Angers, Frankrig, 17/05/2010.

Free Space Computation From Stochastic Occupancy Grids Based On Iconic Kalman Filtered Disparity Maps. / Høilund, Carsten; Moeslund, Thomas B.; Madsen, Claus B.; Trivedi, Mohan M.

International Conference on Computer Vision Theory and Applications (VISAPP). Bind 1 Institute for Systems and Technologies of Information, Control and Communication, 2010. s. 164-167.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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AU - Moeslund, Thomas B.

AU - Madsen, Claus B.

AU - Trivedi, Mohan M.

PY - 2010/5/17

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N2 - This paper presents a method for determining the free space in a scene as viewed by a vehicle-mounted camera.Using disparity maps from a stereo camera and known camera motion, the disparity maps are first filtered by an iconic Kalman filter, operating on each pixel individually, thereby reducing variance and increasing the density of the filtered disparity map. Then, a stochastic occupancy grid is calculated from the filtered disparity map, providing a top-down view of the scene where the uncertainty of disparity measurements are taken into account. These occupancy grids are segmented to indicate a maximum depth free of obstacles, enabling the marking of free space in the accompanying intensity image. The test shows successful marking of free space in the evaluated scenarios in addition to significant improvement in disparity map quality.

AB - This paper presents a method for determining the free space in a scene as viewed by a vehicle-mounted camera.Using disparity maps from a stereo camera and known camera motion, the disparity maps are first filtered by an iconic Kalman filter, operating on each pixel individually, thereby reducing variance and increasing the density of the filtered disparity map. Then, a stochastic occupancy grid is calculated from the filtered disparity map, providing a top-down view of the scene where the uncertainty of disparity measurements are taken into account. These occupancy grids are segmented to indicate a maximum depth free of obstacles, enabling the marking of free space in the accompanying intensity image. The test shows successful marking of free space in the evaluated scenarios in addition to significant improvement in disparity map quality.

M3 - Article in proceeding

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SP - 164

EP - 167

BT - International Conference on Computer Vision Theory and Applications (VISAPP)

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Høilund C, Moeslund TB, Madsen CB, Trivedi MM. Free Space Computation From Stochastic Occupancy Grids Based On Iconic Kalman Filtered Disparity Maps. I International Conference on Computer Vision Theory and Applications (VISAPP). Bind 1. Institute for Systems and Technologies of Information, Control and Communication. 2010. s. 164-167