Building semantic object maps from sparse and noisy 3D data
| Autor: | Joachim Hertzberg, Sven Albrecht, Thomas Wiemann, Martin Günther |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Computer science
business.industry Frame (networking) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Cognitive neuroscience of visual object recognition Point cloud Mobile robot Iterative reconstruction Object (computer science) 3D pose estimation Computer vision Artificial intelligence business Pose |
| Zdroj: | IROS |
| DOI: | 10.1109/iros.2013.6696668 |
| Popis: | We present an approach to create a semantic map of an indoor environment, based on a series of 3D point clouds captured by a mobile robot using a Kinect camera. The proposed system reconstructs the surfaces in the point clouds, detects different types of furniture and estimates their poses. The result is a consistent mesh representation of the environment enriched by CAD models corresponding to the detected pieces of furniture. We evaluate our approach on two datasets totaling over 800 frames directly on each individual frame. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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