UTILIZATION OF SPATIAL INFORMATION FOR POINT CLOUD SEGMENTATION

Date

2010-06-09

Author

Akman, Oytun
Bayramoglu, Neslihan
Alatan, Abdullah Aydın
Jonker, Pieter

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Object segmentation has an important role in the field of computer vision for semantic information inference. Many applications such as 3DTV archive systems, 3D/2D model fitting, object recognition and shape retrieval are strongly dependent to the performance of the segmentation process. In this paper we present a new algorithm for object localization and segmentation based on the spatial information obtained via a Time-of-Flight (TOF) camera. 3D points obtained via a TOF camera are projected onto the major plane representing the planar surface on which the objects are placed. Afterward, the most probable regions that an item can be placed are extracted by using kernel density estimation method and 3D points are segmented into objects. Also some well-known segmentation algorithms are tested on the 3D (depth) images.

Subject Keywords

3D sensor fusion, Segmentation, Density estimation

URI

https://hdl.handle.net/11511/52971

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar