Consistency of robust estimators in multi-structural visual data segmentation
Pattern Recognition
A comparative study of model selection criteria for computer vision applications
Image and Vision Computing
A Multi-agent Approach for Range Image Segmentation
CEEMAS '07 Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V
An Agent-Based Approach for Range Image Segmentation
Massively Multi-Agent Technology
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Journal of Mathematical Imaging and Vision
Range segmentation of large building exteriors: A hierarchical robust approach
Computer Vision and Image Understanding
A multi-agent approach for range image segmentation with Bayesian edge regularization
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
A novel hierarchical technique for range segmentation of large building exteriors
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
A new Bayesian method for range image segmentation
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Bayesian edge regularization in range image segmentation
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Planar background elimination in range images: a practical approach
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptive multi-scale segmentation of surface data using unsupervised learning of seed positions
Engineering Applications of Artificial Intelligence
Complex and photo-realistic scene representation based on range planar segmentation and model fusion
International Journal of Robotics Research
A new distributed approach for range image segmentation
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
| Hi-index | 0.01 |
In this paper, we address the problem of recovering the true underlying model of a surface while performing the segmentation. First, and in order to solve the model selection problem, we introduce a novel criterion, which is based on minimising strain energy of fitted surfaces. We then evaluate its performance and compare it with many other existing model selection techniques. Using this criterion, we then present a robust range data segmentation algorithm capable of segmenting complex objects with planar and curved surfaces. The presented algorithm simultaneously identifies the type (order and geometric shape) of each surface and separates all the points that are part of that surface. This paper includes the segmentation results of a large collection of range images obtained from objects with planar and curved surfaces. The resulting segmentation algorithm successfully segments various possible types of curved objects. More importantly, the new technique is capable of detecting the association between separated parts of a surface, which has the same Cartesian equation while segmenting a scene. This aspect is very useful in some industrial applications of range data analysis.