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Learning-Based Symmetry Detection in Natural Images [chapter]

Stavros Tsogkas, Iasonas Kokkinos
2012 Lecture Notes in Computer Science  
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

Wei Shen, Xiang Bai, Zihao Hu, Zhijiang Zhang
2016 Pattern Recognition  
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]

Shobhita Sundaram, Darius Sinha, Matthew Groth, Tomotake Sasaki, Xavier Boix
2022 arXiv   pre-print
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

John P. Swaddle, Douglas A. Ruff, Laura C. Page, Alicia M. Frame, Victoria A. Long
2008 Animal Behaviour  
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

Jong Hyuk Park
2020 Symmetry  
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]

Yukang Wang, Yongchao Xu, Stavros Tsogkas, Xiang Bai, Sven Dickinson, Kaleem Siddiqi
2018 arXiv   pre-print
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]

Yifei Shi, Junwen Huang, Hongjia Zhang, Xin Xu, Szymon Rusinkiewicz, Kai Xu
2020 arXiv   pre-print
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]

Yeman Brhane Hagos, Albert Gubern Mérida, Jonas Teuwen
2018 Lecture Notes in Computer Science  
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

Joost Willemse, Michiel van der Vaart, Wen Yang, Ariane Briegel
2020 Microscopy and Microanalysis  
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

Christopher Funk, Seungkyu Lee, Martin R. Oswald, Stavros Tsogkas, Wei Shen, Andrea Cohen, Sven Dickinson, Yanxi Liu
2017 2017 IEEE International Conference on Computer Vision Workshops (ICCVW)  
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

Francisco Bonnin-Pascual, Alberto Ortiz
2014 Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)  
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

Jui-Yuan Su, Shyi-Chyi Cheng, De-Kai Huang
2015 Symmetry  
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]

Shubham Tulsiani, Abhishek Kar, Qixing Huang, João Carreira and Jitendra Malik
2015 arXiv   pre-print
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]

Florian Baumann, Katharina Ernst, Arne Ehlers, Bodo Rosenhahn
2010 Lecture Notes in Computer Science  
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

Wei Ke, Jie Chen, Jianbin Jiao, Guoying Zhao, Qixiang Ye
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
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
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