Integrating Visual and Range Data for Robotic Object Detection
Date
2008
Authors
Gould, Stephen
Baumstarck, Paul
Quigley, Morgan
Ng, Andrew Y.
Koller, Daphne
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
The problem of object detection and recognition is a notoriously difficult one, and one that has been the focus of much work in the computer vision and robotics communities. Most work has concentrated on systems that operate purely on visual inputs (i.e. , images) and largely ignores other sensor modalities. However, despite the great progress made down this track, the goal of high accuracy object detection for robotic platforms in cluttered real-world environments remains elusive. Instead of relying on information from the image alone, we present a method that exploits the multiple sensor modalities available on a robotic platform. In particular, our method augments a 2-d object detector with 3-d information from a depth sensor to produce a �multi-modal object detector.� We demonstrate our method on a working robotic system and evaluate its performance on a number of common household/office objects.
Description
Keywords
Citation
Collections
Source
Proceedings of European Conference on Computer Vision (ECCV 2008)
Type
Conference paper
Book Title
Entity type
Access Statement
License Rights
DOI
Restricted until
2037-12-31
Downloads
File
Description