Spatial grouping of 3D points from multiple stereovision sensors

Author

Nedevschi, S. ; Danescu, R. ; Frentiu, D. ; Marita, T. ; Oniga, F. ; Pocol, C.

Author_Institution

Dept. of Comput. Sci., Cluj-Napoca Tech. Univ., Romania

Volume

2

fYear

2004

fDate

21-23 March 2004

Firstpage

874

Abstract

This paper presents a method for grouping 3D points into cuboids. The 3D points are extracted using multiple stereovision sensors, and the sensor fusion module performs the fusion of the data sets and the grouping of the points in a single algorithm. The fusion/grouping algorithm is scalable, being able to work using any number of sensors, including a single one. The grouping method relies on a method of transforming the 3D space so that the density of the points is kept constant, and all the points belonging to a single object are adjacent, making the grouping of points into cuboids a simple labeling problem.

Keywords

feature extraction; image sensors; sensor fusion; stereo image processing; 3D point extraction; data fusion; distributed computation; feature grouping; fusion algorithm; grouping algorithm; multiple stereovision sensors; sensor fusion module; simple labeling problem; spatial grouping; Computer science; Data mining; Distributed computing; Labeling; Laser radar; Layout; Sensor fusion; Sensor systems; Shape; Spatial coherence;

fLanguage

English

Publisher

ieee

Conference_Titel

Networking, Sensing and Control, 2004 IEEE International Conference on

ISSN

1810-7869

Print_ISBN

0-7803-8193-9

Type

conf

DOI

10.1109/ICNSC.2004.1297062

Filename

1297062