An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Adaptive Segmentation of Range Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Extracting a Valid Boundary Representation from a Segmented Range Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Complex Scenes Segmentation from a Single Range Image Using Virtual Exploration
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Exploration trees on highly complex scenes: A new approach for 3D segmentation
Pattern Recognition
A new digital watermarking scheme for 3D triangular mesh models
Signal Processing
A relational vector space model using an advanced weighting scheme for image retrieval
Information Processing and Management: an International Journal
3D scene retrieval and recognition with Depth Gradient Images
Pattern Recognition Letters
| Hi-index | 0.10 |
This paper presents a new strategy to extract knowledge about the objects and their relative location in a complex scene when a single range image is taken. The analysis process is based on a range data distributed segmentation technique, which separates the components of the scene, and on a silhouette segmentation method, which classified the silhouette in real (non occluded) and false (occluded) parts. Finally, an occlusion graph provides a compact representation about the layout and relationship of the objects in the scene. This information is essential before higher level tasks in complex scenes - like recognition, understanding and robot interaction - are carried out. An extensive experimentation has been accomplished under real conditions in scenes of up to 12 objects yielding a very good performance. The experiments and results carried out validate the goodness of this approach in 3D environments.