A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
Filters
Learning-Based Symmetry Detection in Natural Images
[chapter]
2012
Lecture Notes in Computer Science
Preserved Fulltext
In this work we propose a learning-based approach to symmetry detection in natural images. ...
We focus on ribbon-like structures, i.e. contours marking local and approximate reflection symmetry and make three contributions to improve their detection. ...
In this work we develop a learning-based approach to detect symmetry axes in natural images. ...
doi:10.1007/978-3-642-33786-4_4
fatcat:ts3ommyzq5dfpjxc6mrprjtffy
Multiple instance subspace learning via partial random projection tree for local reflection symmetry in natural images
2016
Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Local reflection symmetry detection in nature images is a quite important but challenging task in computer vision. ...
In this paper, we propose a novel multiple instance learning framework for local reflection symmetry detection, named multiple instance subspace learning (MISL), which instead learns a group of models ...
Methodology In this section, we introduce our approach to detect symmetries in natural images. ...
doi:10.1016/j.patcog.2015.10.015
fatcat:vfmwyvbgsjelndhn3rvuu2u56u
Symmetry Perception by Deep Networks: Inadequacy of Feed-Forward Architectures and Improvements with Recurrent Connections
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Symmetry is omnipresent in nature and perceived by the visual system of many species, as it facilitates detecting ecologically important classes of objects in our environment. ...
In this paper, we evaluate Deep Neural Network (DNN) architectures on the task of learning symmetry perception from examples. ...
Evidently, more investigation of generalizable detection of symmetry in natural images is needed. ...
arXiv:2112.04162v2
fatcat:ibdykd7kyzbd5jebktlvx5fkcy
A test of receiver perceptual performance: European starlings' ability to detect asymmetry in a naturalistic trait
2008
Animal Behaviour
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2010; you can also visit the original URL.
The file type is application/pdf.
Through a series of operant learning trials, we trained starlings to discriminate symmetry from an initially large asymmetry (50% relative asymmetry in the position and number of dots) and then reduced ...
We discuss this limit in light of natural plumage asymmetries and conclude that most individuals in a wild population would probably be perceived as equally 'symmetric', rendering FA in such a trait an ...
Symmetry Detection Learning Trials Every bird began the learning phase of the experiment by being reinforced to detect the symmetric images from the 50% asymmetric images. ...
doi:10.1016/j.anbehav.2008.05.005
fatcat:lf6n3b6jwbbabkzzp3njjs2ri4
Symmetry-Adapted Machine Learning for Information Security
2020
Symmetry
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The symmetry-adapted machine-learning approach can support an effective way to deal with the dynamic nature of security attacks by the extraction and analysis of data to identify hidden patterns of data ...
Therefore, we accepted twelve articles for this Special Issue that explore the deployment of symmetry-adapted machine learning for information security in various application areas. ...
The autonomous nature of symmetry-adapted machine-learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authority. ...
doi:10.3390/sym12061044
fatcat:dury4tukzre7hblsusdxcg4zee
DeepFlux for Skeletons in the Wild
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Many recent methods frame object skeleton detection as a binary pixel classification problem, which is similar in spirit to learning-based edge detection, as well as to semantic segmentation methods. ...
Computing object skeletons in natural images is challenging, owing to large variations in object appearance and scale, and the complexity of handling background clutter. ...
Learning-based methods [19, 40, 45, 33, 42] have an improved ability for object skeleton detection in natural images, but such methods are still unable to cope with complex backgrounds or clutter. ...
arXiv:1811.12608v1
fatcat:pahjsjqtfbhzbmaawn4yd3ktxq
SymmetryNet: Learning to Predict Reflectional and Rotational Symmetries of 3D Shapes from Single-View RGB-D Images
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In addition, our network is able to detect for a given shape multiple symmetries of different types. We also contribute a benchmark of 3D symmetry detection based on single-view RGB-D images. ...
We study the problem of symmetry detection of 3D shapes from single-view RGB-D images, where severely missing data renders geometric detection approach infeasible. ...
We are grateful to Yao Duan, Dengsheng Chen and Yuqing Lan for their discussion in data preparation. ...
arXiv:2008.00485v3
fatcat:tjm7fpxdgrd4xeicwyis6dgtze
Improving Breast Cancer Detection Using Symmetry Information with Deep Learning
[chapter]
2018
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this work, we proposed a patch based multi-input CNN that learns symmetrical difference to detect breast masses. The network was trained on a large-scale dataset of 28294 mammogram images. ...
Convolutional Neural Networks (CNN) have had a huge success in many areas of computer vision and medical image analysis. ...
Nowadays, with a massive amount of data and computational power, Deep Learning (DL) has shown a remarkable success in natural language processing [6] and object detection and recognition [7] . ...
doi:10.1007/978-3-030-00946-5_10
fatcat:bqctfv4sqndknh5tbpq3nbh4je
Mathematical Mirroring for Identification of Local Symmetry Centers in Microscopic Images Local Symmetry Detection in FIJI
2020
Microscopy and Microanalysis
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Symmetry is omnipresent in nature and we encounter symmetry routinely in our everyday life. ...
Though there are already many methods available to detect symmetry in images, to the best of our knowledge, our algorithm is the first that is easily applicable in ImageJ/FIJI. ...
We thank Gerda Lamers for the useful discussions on this subject, as well as for the suggestions on which biological images this could be used. ...
doi:10.1017/s1431927620024320
pmid:32878652
fatcat:pbeyxuh3aveulcopiepyd6lsgm
2017 ICCV Challenge: Detecting Symmetry in the Wild
2017
2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Motivated by various new applications of computational symmetry in computer vision and in an effort to advance machine perception of symmetry in the wild, we organize the third international symmetry detection ...
In this report, we provide a detailed summary of our evaluation methodology for each type of symmetry detection algorithm validated. ...
This work is supported in part by an US NSF CREATIV grant (IIS-1248076), NSERC Canada, and an National Natural Science Foundation of China grant (No. 61672336). ...
doi:10.1109/iccvw.2017.198
dblp:conf/iccvw/FunkLOTSCDL17
fatcat:jbj2fad3rrbcrl2spcdzn2gwl4
A probabilistic approach for defect detection based on saliency mechanisms
2014
Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The visual information is suggested to be based on features commonly used to predict human eye fixations: contrast and symmetry. ...
The use of saliency mechanisms for defect detection is discussed in this work. We consider defects on regular surfaces as conspicuous areas that catch the attention of the surveyors. ...
They call their framework Saliency Using Natural Statistics (SUN) since they focus on learned statistics from natural scenes. ...
doi:10.1109/etfa.2014.7005257
dblp:conf/etfa/Bonnin-PascualO14
fatcat:jsartjjssjcntc64xwe4b4kp3i
Unsupervised Object Modeling and Segmentation with Symmetry Detection for Human Activity Recognition
2015
Symmetry
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
In this paper we present a novel unsupervised approach to detecting and segmenting objects as well as their constituent symmetric parts in an image. ...
Finally, for each detected object, the graphcut-based segmentation algorithm is applied to find its contour. ...
Acknowledgments This work was supported in part by Ministry of Science and Technology, Taiwan under Grant Number MOST 103-2221-E-019-018-MY2. ...
doi:10.3390/sym7020427
fatcat:o6ajgjqagrczvgqdb63hilnroa
Shape and Symmetry Induction for 3D Objects
[article]
2015
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this paper we repurpose powerful learning machinery, originally developed for object classification, to discover image cues relevant for recovering the 3D shape of potentially unfamiliar objects. ...
We cast the problem as one of local prediction of surface normals and global detection of 3D reflection symmetry planes, which open the door for extrapolating occluded surfaces from visible ones. ...
Acknowledgements This work was supported in part by NSF Award IIS-1212798 and ONR MURI-N00014-10-1-0933. Shubham Tulsiani was supported by the Berkeley fellowship. ...
arXiv:1511.07845v2
fatcat:jpmjzjuofrbflo7t3tvb222qhy
Symmetry Enhanced Adaboost
[chapter]
2010
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf.
This paper describes a method to minimize the immense training time of the conventional Adaboost learning algorithm in object detection by reducing the sampling area. ...
Symmetry enhanced Adaboost (SEAdaboost) can limit the scanning area enormously, depending on the degree of the objects symmetry, while it maintains the detection rate. ...
By incorporating the idea of symmetry in the conventional Adaboost algorithm and the thereby reduced sampling area, Symmetry enhanced Adaboost effectively stabilizes learning results. ...
doi:10.1007/978-3-642-17289-2_28
fatcat:pctr4ijobfgfvbekuh75otqx6i
SRN: Side-Output Residual Network for Object Symmetry Detection in the Wild
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
symmetry detection in the wild. ...
In this paper, we establish a baseline for object symmetry detection in complex backgrounds by presenting a new benchmark and an end-to-end deep learning approach, opening up a promising direction for ...
Acknowledgement This work is supported in partial by the NSFC under ...
doi:10.1109/cvpr.2017.40
dblp:conf/cvpr/KeCJZY17
fatcat:e7upwfjwmbe73cqlvsthw26jhe
« Previous
Showing results 1 — 15 out of 44,951 results