Abstract
Stereo vision systems in a Robotic navigation environment determine the depth in the form of a depth map image from two or more images which are taken at the same time, but from slightly different viewpoints. Ground suppression from depth map is essential for object reconstruction in 3D environment as the ground surface is considered as traveling medium than as an object. Ground separated depth map needs to be segmented to identify the objects of interest. Objects identified below the threshold size need to be removed from the scene. In this paper we propose a Fuzzy-based parallel object clustering algorithm to reconstruct the objects of interest in 3D environment from the ground suppressed depth map. The depth map is divided into Fuzzy layers in X-Z plane and these Fuzzy layers are processed in parallel to reconstruct the objects of interest in 3D environment using region growing method on a cluster computing setup. Experimental results show that Fuzzy logic effectively handles the uncertainty in object reconstruction process. The parallel implementation of the algorithm drastically reduces the time required for object reconstruction process in congested navigational environments.
| Original language | English |
|---|---|
| Title of host publication | 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 |
| Pages | 816-821 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 01-12-2010 |
| Event | 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 - Singapore, Singapore Duration: 07-12-2010 → 10-12-2010 |
Conference
| Conference | 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 |
|---|---|
| Country | Singapore |
| City | Singapore |
| Period | 07-12-10 → 10-12-10 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Control and Systems Engineering
Cite this
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Parallel implementation of 3D object reconstruction in a robotic navigational environment. / Rajpurohit, Vijay S.; Manohara Pai, M. M.
11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010. 2010. p. 816-821 5707767.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Parallel implementation of 3D object reconstruction in a robotic navigational environment
AU - Rajpurohit, Vijay S.
AU - Manohara Pai, M. M.
PY - 2010/12/1
Y1 - 2010/12/1
N2 - Stereo vision systems in a Robotic navigation environment determine the depth in the form of a depth map image from two or more images which are taken at the same time, but from slightly different viewpoints. Ground suppression from depth map is essential for object reconstruction in 3D environment as the ground surface is considered as traveling medium than as an object. Ground separated depth map needs to be segmented to identify the objects of interest. Objects identified below the threshold size need to be removed from the scene. In this paper we propose a Fuzzy-based parallel object clustering algorithm to reconstruct the objects of interest in 3D environment from the ground suppressed depth map. The depth map is divided into Fuzzy layers in X-Z plane and these Fuzzy layers are processed in parallel to reconstruct the objects of interest in 3D environment using region growing method on a cluster computing setup. Experimental results show that Fuzzy logic effectively handles the uncertainty in object reconstruction process. The parallel implementation of the algorithm drastically reduces the time required for object reconstruction process in congested navigational environments.
AB - Stereo vision systems in a Robotic navigation environment determine the depth in the form of a depth map image from two or more images which are taken at the same time, but from slightly different viewpoints. Ground suppression from depth map is essential for object reconstruction in 3D environment as the ground surface is considered as traveling medium than as an object. Ground separated depth map needs to be segmented to identify the objects of interest. Objects identified below the threshold size need to be removed from the scene. In this paper we propose a Fuzzy-based parallel object clustering algorithm to reconstruct the objects of interest in 3D environment from the ground suppressed depth map. The depth map is divided into Fuzzy layers in X-Z plane and these Fuzzy layers are processed in parallel to reconstruct the objects of interest in 3D environment using region growing method on a cluster computing setup. Experimental results show that Fuzzy logic effectively handles the uncertainty in object reconstruction process. The parallel implementation of the algorithm drastically reduces the time required for object reconstruction process in congested navigational environments.
UR - http://www.scopus.com/inward/record.url?scp=79952427045&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952427045&partnerID=8YFLogxK
U2 - 10.1109/ICARCV.2010.5707767
DO - 10.1109/ICARCV.2010.5707767
M3 - Conference contribution
SN - 9781424478132
SP - 816
EP - 821
BT - 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
ER -