On the performance of connected components grouping

International Journal of Computer Vision

Volumn 41, Issue 3, 2001, Pages 195-216

  Berengolts, Alexander ^a   Lindenbaum, Michael ^a  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Connected components algorithm; Grouping performance analysis; Perceptual organization; Quantitative predictions

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTATIONAL METHODS; ERROR ANALYSIS; GRAPH THEORY; MATHEMATICAL MODELS; PROBABILITY;

CONNECTED COMPONENTS ALGORITHM; GROUPING PERFORMANCE ANALYSIS; PERCEPTUAL ORGANIZATION; QUANTITATIVE PREDICTIONS;

COMPUTER VISION;

EID: 0035244990     PISSN: 09205691     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1011108121495     Document Type: Article

References (28)

1. A generic grouping algorithm and its quantitative analysis
2. Special issue on perceptual organization in computer vision
3. Percolation process I. Crystals and mazes
4. Space and time bounds on indexing 3-D models from 2-D images
5. Curve-like sets, normal complexity, and representation
6. Use of the hough transform to detect lines and curves in pictures
7. On the evolution of random graphs
8. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
9. Figure-ground discrimination: A combinatorial optimization approach
10. Recognizing solid objects by alignment with an image
11. The use of grouping in visual object recognition
12. Robust and efficient detection of salient convex groups
13. Perceptual organization for scene segmentation and description
14. Random perturbation models for boundary extraction sequence
15. B-spline contour representation and symmetry detection
16. Perceptual organization in computer vision: A review and proposal for a classifactory structure
17. Structural saliency: The detection of globally salient structures using locally connected network
18. Decomposition of two-dimentional shapes by graph-theoretic clustering
19. Normalized cuts and image sementation
20. On the role of structure in vision