3D Object Mapping by Integrating Stereo SLAM and Object Segmentation Using Edge Points

Authors:
Masahiro Tomono
Affiliations:
Chiba Institute of Technology, Chiba, Japan 275-0016
Venue:
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Year:
2009

Citing 13
Cited 0

A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes

IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Feature Detection with Automatic Scale Selection

International Journal of Computer Vision
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

Communications of the ACM
Shape Indexing Using Approximate Nearest-Neighbour Search in High-Dimensional Spaces

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Spatial Weighting for Bag-of-Features

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Using Multiple Segmentations to Discover Objects and their Extent in Image Collections

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
3D Object Modeling and Segmentation Based on Edge-Point Matching with Local Descriptors

ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Robust 3D SLAM with a stereo camera based on an edge-point ICP algorithm

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Unsupervised identification of multiple objects of interest from multiple images: dISCOVER

ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a method of 3D object mapping using a binocular stereo camera. The method employs edge points as map element to represent detailed shape and applies a variant of ICP algorithm to 3D mapping. A SIFT descriptor is attached to each edge point for object recognition and segmentation. The 3D map is segmented into individual objects using training images of target objects with different backgrounds based on SIFT-based 2D and 3D matching. In experiments, a detailed 3D map was built by the stereo SLAM and a 3D object map was created through the segmentation of the 3D map into 36 object instances.