A Framework for Performance Characterization of Intermediate-Level Grouping Modules
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation from consensus information
Computer Vision and Image Understanding
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Boundaries in Natural Images: A New Method Using Point Descriptors and Area Completion
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Spectral Partitioning with Indefinite Kernels Using the Nyström Extension
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Segmentation by Grouping Junctions
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Image Segmentation Using Local Variation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Textons, Contours and Regions: Cue Integration in Image Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
An empirical approach to grouping and segmentation
An empirical approach to grouping and segmentation
Multiclass Spectral Clustering
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Learning and Inferring Image Segmentations using the GBP Typical Cut Algorithm
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Spectral Grouping Using the Nyström Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation Induced by Scale Invariance
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Quantitative Evaluation of a Novel Image Segmentation Algorithm
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Advances in computational image segmentation and perceptual grouping
Advances in computational image segmentation and perceptual grouping
Learning to segment images using region-based perceptual features
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Image segmentation with ratio cut
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color image segmentation using pixel wise support vector machine classification
Pattern Recognition
Detecting spatiotemporal structure boundaries: beyond motion discontinuities
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
LS-SVM based image segmentation using color and texture information
Journal of Visual Communication and Image Representation
Color texture segmentation based on image pixel classification
Engineering Applications of Artificial Intelligence
Salient object detection: a benchmark
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Spectral Image Segmentation Using Image Decomposition and Inner Product-Based Metric
Journal of Mathematical Imaging and Vision
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We present a thorough quantitative evaluation of four image segmentation algorithms on images from the Berkeley Segmentation Database. The algorithms are evaluated using an efficient algorithm for computing precision and recall with regard to human ground-truth boundaries. We test each segmentation method over a representative set of input parameters, and present tuning curves that fully characterize algorithm performance over the complete image database. We complement the evaluation on the BSD with segmentation results on synthetic images. The results reported here provide a useful benchmark for current and future research efforts in image segmentation.