Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to Computer Graphics
Introduction to Computer Graphics
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
3D Recognition and Segmentation of Objects in Cluttered Scenes
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Contour-Based Object Detection in Range Images
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Instance-based AMN classification for improved object recognition in 2D and 3D laser range data
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Combined 2D-3D categorization and classification for multimodal perception systems
International Journal of Robotics Research
GPGPU implementation of growing neural gas: Application to 3D scene reconstruction
Journal of Parallel and Distributed Computing
Integrating multiple viewpoints for articulated scene model aquisition
ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
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A mobile robot that accomplishes high level tasks needs to be able to classify the objects in the environment and to determine their location. In this paper, we address the problem of online object detection in 3D laser range data. The object classes are represented by 3D point-clouds that can be obtained from a set of range scans. Our method relies on the extraction of point features from range images that are computed from the point-clouds. Compared to techniques that directly operate on a full 3D representation of the environment, our approach requires less computation time while retaining the robustness of full 3D matching. Experiments demonstrate that the proposed approach is even able to deal with partially occluded scenes and to fulfill the runtime requirements of online applications.