scholarly journals Single View Metrology in the Wild

2020 ◽  
pp. 316-333
Author(s):  
Rui Zhu ◽  
Xingyi Yang ◽  
Yannick Hold-Geoffroy ◽  
Federico Perazzi ◽  
Jonathan Eisenmann ◽  
...  
Keyword(s):  
Single View ◽  
In The Wild ◽  
Single View Metrology

Study on fabric compression under seam vis a vis quantitative measurement of seam boldness and thread consumption for lockstitch 301

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Md Vaseem Chavhan ◽  
Mandapati Ramesh Naidu
Keyword(s):  
Quantitative Measurement ◽  
Multilinear Regression ◽  
New Approach ◽  
Content Type ◽  
Single View ◽  
Sewing Thread ◽  
Stitch Density ◽  
Proposed Model ◽  
Fabric Weight ◽  
Single View Metrology

Purpose This paper aims to develop at sewing thread during the seam formation may lead to the compression of fabric under seam. In the present study, the model has been proposed to predict the seam compression and calculation of seam boldness, as well as thread consumption by considering seam compression. Design/methodology/approach The effect of sewing parameters on the fabric compression at the seam (Cf) for fabrics of varying bulk density was studied by the Taguchi method and also the multilinear regression equation is obtained to predict seam compression by considering these parameters. The framework has been set as per the single view metrology approach to measuring structural seam boldness (Bs). One of the basic geometrical models (Ghosh and Chavhan, 2014) for the prediction of thread consumption at lock stitch has been modified by considering fabric compression at the seam (Cf). Findings The multilinear regression model has been proposed which can predict the compression under seam using easily measurable fabric parameters and stitch density. The seam boldness is successfully calculated quantitatively using the proposed formula with a good correlation with the seam boldness rated subjectively. The thread consumption estimation from the proposed approach was found to be more accurate. Originality/value The compression under seam is found out using easily measurable parameters; fabric thickness, fabric weight and stitch density from the proposed model. The attempt has been made to calculate seam boldness quantitatively and the new approach to find out thread consumption by considering the seam compression has been proposed.

Single View Metrology Along Orthogonal Directions

2010 ◽  
Author(s):  
Kun Peng ◽  
Lulu Hou ◽  
Ren Ren ◽  
Xianghua Ying ◽  
Hongbin Zha
Keyword(s):  
Single View ◽  
Single View Metrology

scholarly journals Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild (Extended Abstract)

2021 ◽  
Author(s):  
Shangzhe Wu ◽  
Christian Rupprecht ◽  
Andrea Vedaldi
Keyword(s):  
Input Image ◽  
Shape Model ◽  
Single View ◽  
Model Code ◽  
3D Objects ◽  
Object Categories ◽  
Symmetric Structure ◽  
In The Wild ◽  
Human Faces ◽  
Prior Shape

We propose a method to learn 3D deformable object categories from raw single-view images, without external supervision. The method is based on an autoencoder that factors each input image into depth, albedo, viewpoint and illumination. In order to disentangle these components without supervision, we use the fact that many object categories have, at least approximately, a symmetric structure. We show that reasoning about illumination allows us to exploit the underlying object symmetry even if the appearance is not symmetric due to shading. Furthermore, we model objects that are probably, but not certainly, symmetric by predicting a symmetry probability map, learned end-to-end with the other components of the model. Our experiments show that this method can recover very accurately the 3D shape of human faces, cat faces and cars from single-view images, without any supervision or a prior shape model. Code and demo available at https://github.com/elliottwu/unsup3d.

Single view metrology of wide-angle lens images

2006 ◽  
Vol 22 (7) ◽  
pp. 445-455 ◽  
Author(s):  
Yisong Chen ◽  
Horace H.S. Ip
Keyword(s):  
Wide Angle ◽  
Single View ◽  
Wide Angle Lens ◽  
Single View Metrology

Single view metrology from scene constraints

2005 ◽  
Vol 23 (9) ◽  
pp. 831-840 ◽  
Author(s):  
Guanghui Wang ◽  
Zhanyi Hu ◽  
Fuchao Wu ◽  
Hung-Tat Tsui
Keyword(s):  
Single View ◽  
Single View Metrology
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