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Interactive Image Segmentation Using Constrained Dominant Sets
[article]
2016
arXiv
pre-print
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We propose a new approach to interactive image segmentation based on some properties of a family of quadratic optimization problems related to dominant sets, a well-known graph-theoretic notion of a cluster ...
clusters which are constrained to contain user-selected elements. ...
Conclusions In this paper, we have developed an interactive image segmentation algorithm based on the idea of finding a collection of dominant-set clusters constrained to contain the elements of a user ...
arXiv:1608.00641v2
fatcat:qtdoaozpwbba3meto7hr5soiaq
Interactive Image Segmentation Using Constrained Dominant Sets
[chapter]
2016
Lecture Notes in Computer Science
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We propose a new approach to interactive image segmentation based on some properties of a family of quadratic optimization problems related to dominant sets, a well-known graph-theoretic notion of a cluster ...
clusters which are constrained to contain user-selected elements. ...
Conclusions In this paper, we have developed an interactive image segmentation algorithm based on the idea of finding a collection of dominant-set clusters constrained to contain the elements of a user ...
doi:10.1007/978-3-319-46484-8_17
fatcat:pye3hglzqzd43bbjgbgljxmxay
Constrained Dominant sets and Its applications in computer vision
[article]
2020
arXiv
pre-print
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In this thesis, we present new schemes which leverage a constrained clustering method to solve several computer vision tasks ranging from image retrieval, image segmentation and co-segmentation, to person ...
Sets. ...
Multi-features Fusion Using Constrained Dominant Sets for Image Retrieval
.1. Multi-features Fusion Using Constrained Dominant Sets for Image Retrieval ...
arXiv:2002.06028v1
fatcat:rxf5idn2fjcvzj24iu4kggbaoq
Weakly Supervised Semantic Segmentation Using Constrained Dominant Sets
[chapter]
2019
Lecture Notes in Computer Science
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2019 pre-print arXiv:1909.09414v1 fatcat:y367w2cftfb43jcpoamkmbufvu
In this work, we explore the potential of Constrained Dominant Sets (CDS) for generating multi-labeled full mask predictions to train a fully convolutional network (FCN) for semantic segmentation. ...
The availability of large-scale data sets is an essential pre-requisite for deep learning based semantic segmentation schemes. ...
Constrained Dominant Sets Dominant Set Framework. ...
doi:10.1007/978-3-030-30645-8_39
fatcat:zbdzkwa6yfavjhxefpomhexs3a
Dominant Sets for "Constrained" Image Segmentation
2018
IEEE Transactions on Pattern Analysis and Machine Intelligence
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., some form of user assistance (interactive segmentation) or ask for the simultaneous segmentation of two or more images (co-segmentation). ...
In particular, we shall focus on interactive segmentation and co-segmentation (in both the unsupervised and the interactive versions). ...
Given the affinity matrix, we used replicator dynamics (12) to exctract constrained dominant sets. ...
doi:10.1109/tpami.2018.2858243
pmid:30040623
fatcat:wlo5jf7mzfh3jlww7mbzpblgpq
AN INTERACTIVE IMAGE SEGMENTATION USING MULTIPLE USER INPUTªS
2013
International Journal of Research in Engineering and Technology
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Interactive image segmentation involves a proposed algorithm, Constrained Random walks algorithm. The Constrained Random Walks algorithm facilitates the use of three types of user inputs. 1. ...
In this paper, we consider the Interactive image segmentation with multiple user inputs. The proposed system is the use of multiple intuitive user inputs to better reflect the user's intention. ...
The extension is known as constrained random walks algorithm to facilitate the use of various user inputs in interactive image segmentation. ...
doi:10.15623/ijret.2013.0203016
fatcat:ivzut2damvcarpfpph5u5v35fq
Robust interactive image segmentation via iterative refinement
2014
2014 IEEE International Conference on Image Processing (ICIP)
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However, existing interactive image segmentation methods still might fail if the image contains messy textures, or the user inputs are sparse or at inappropriate locations. ...
Extensive experiments using real world images, and segmentation benchmark dataset show that our proposed method has superior performance compared with representative state-of-the-art methods. ...
[11] extended it to interactive image segmentation, which is named constrained active contour model. ...
doi:10.1109/icip.2014.7025889
dblp:conf/icip/PengZYZF14
fatcat:swqyxu5awvfv5iurbaaadtcs24
Automatic corpus callosum segmentation using a deformable active Fourier contour model
2012
Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging
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A multi-step optimization strategy, with two constrained steps and a final unconstrained step, is then applied. If needed, interactive segmentation can be performed via contour repulsion points. ...
Using MNI space aligned T1w MRI data, the CC segmentation is initialized on the mid-sagittal plane using the tissue segmentation. ...
Interactive use of repulsion points The automatic segmentation may not be fully accurate in certain areas of the corpus callosum, due to variations in shape but also other issues related to MRI brain images ...
doi:10.1117/12.911504
pmid:24353382
pmcid:PMC3864934
fatcat:nn7j4urolrfwzmu63h34otd44i
Building and Assessing a Constrained Clustering Hierarchical Algorithm
[chapter]
2008
Lecture Notes in Computer Science
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., spatial interactions. A constrained hierarchical agglomerative algorithm with an aggregation index is introduced which uses neighbouring relations present in the data. ...
Unsupervised classification or clustering has been used in many disciplines and contexts. ...
This information could be obtained, e.g., applying an edge detector to the image. ...
doi:10.1007/978-3-540-85920-8_26
fatcat:eydu25ct25aybphwg7xwdhj34y
Robust Interactive Image Segmentation Using Convex Active Contours
2012
IEEE Transactions on Image Processing
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Experimental results on a benchmark data set show that the proposed tool is highly effective and outperforms the state-of-the-art interactive image segmentation algorithms. ...
Index Terms-Interactive image segmentation, convex active contour, digital image editing. ...
The above observations motivate us to design a new method for interactive image segmentation. ...
doi:10.1109/tip.2012.2191566
pmid:22453637
fatcat:6mw2n7hukrd3hcpmkt46a3uz24
3D Kidney Segmentation from CT Images Using a Level Set Approach Guided by a Novel Stochastic Speed Function
[chapter]
2011
Lecture Notes in Computer Science
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The segmentation approach was evaluated on 21 CT data sets with available manual expert segmentation. ...
This paper describes a new 3-D segmentation approach for the kidney from computed tomography (CT) images. ...
Approximate the empirical gray level distribution by using the LCDG with two dominant Gaussian modes. 3. Form an initial region map m using the estimated LCDG models. 4. ...
doi:10.1007/978-3-642-23626-6_72
fatcat:pmlapskxy5cazehrjegobpnaam
IRIS—Intelligent Rapid Interactive Segmentation for Measuring Liver Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease
2022
Tomography
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Methods: SmartClick and antiSmartClick were developed using iterative region growth guided by spatial and intensity connections and were integrated with automated level set (LS) segmentation and graphical ...
Purpose: To develop and integrate interactive features with automatic methods for accurate liver cyst segmentation in patients with autosomal dominant polycystic kidney and liver disease (ADPKD). ...
Conclusions In summary, intelligent rapid interactive segmentation (IRIS) is feasible for fast and accurate liver cyst segmentation in autosomal dominant polycystic kidney disease (ADPKD), using SmartClick ...
doi:10.3390/tomography8010037
pmid:35202202
pmcid:PMC8877996
fatcat:5bwm6q4dajahjn3q6p5m7nphwu
Moment Constraints in Convex Optimization for Segmentation and Tracking
[chapter]
2013
Advanced Topics in Computer Vision
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GPU-based computation times of around 1 second allow for interactive segmentation. ...
Quantitative segmentation studies on a variety of images demonstrate that the user can impose such constraints with a few mouse clicks, leading to substantial improvements of the resulting segmentation ...
Efficient GPU-accelerated PDE solvers allow for computation times of about one second for images of size 300 × 400, making this a practical tool for interactive image segmentation. 1 . 1 Set u := u 0 , ...
doi:10.1007/978-1-4471-5520-1_8
dblp:series/acvpr/KlodtSC13
fatcat:hoeng5wc65h6fpn6tfbqbwxrmq
Automatic video segmentation using spatiotemporal T-junctions
2006
Procedings of the British Machine Vision Conference 2006
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Classical video segmentation algorithms approach the problem from one of two perspectives. At one extreme, global approaches constrain the camera motion to simplify the image structure. ...
Graph cut is then used to segment each frame of the video showing that sparse occlusion edge information can automatically initialize the video segmentation problem. ...
Interactive video cutout by Wang and Cohen extends a frame-wise 2D colour over-segmentation over time using graph cut and user interaction through a novel volumetric painting interface [34] . ...
doi:10.5244/c.20.111
dblp:conf/bmvc/ApostoloffF06
fatcat:fayefoebejaf7fle2ziooeb7h4
Deep Constrained Dominant Sets for Person Re-identification
[article]
2019
arXiv
pre-print
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2019 pre-print arXiv:1904.11397v1 fatcat:ixaiuczhvvdmzkz247fyfj7tjq
To overcome this, we propose an intriguing scheme which treats person-image retrieval problem as a constrained clustering optimization problem, called deep constrained dominant sets (DCDS). ...
By optimizing the constrained clustering in an end-to-end manner, we naturally leverage the contextual knowledge of a set of images corresponding to the given person-images. ...
[40] presented CDS with its applications to interactive Image segmentation. Following, [39] uses CDS to tackle both image segmentation and co-segmentation in interactive and unsupervised setup. ...
arXiv:1904.11397v2
fatcat:ztvu33hvezgqzo2o63lnjrkjfq
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