Year: 2013
Type: article
Abstract: We present a computational framework for the detection of unknown objects in a 3D environment. It is based on a visual attention system that detects proto-objects which are improved by iterative segmentation steps. At the same time a 3D scene model is built from measurements of a depth camera. The detected proto-objects are projected into the 3D scene, resulting in 3D object models which are incrementally updated. Finally, environment- and object-based inhibition of return enables to withdraw the attention from one object and switch to the next. We show that the system works well in cluttered natural scenes and can find and segment objects without prior knowledge.
Authors: Germán Martín García, Simone Frintrop
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2394718694