Face Modeling

2011 ◽  
pp. 45-91
Author(s):  
Daijin Kim ◽  
Jaewon Sung
Keyword(s):  
Computer Vision ◽  
Active Contour ◽  
Face Modeling ◽  
Parametric Curves ◽  
Deformable Template ◽  
Reasonable Amount ◽  
Specific Object ◽  
Specific Shape ◽  
Set Of Points ◽  
Shape Deformations

In the field of computer vision, researchers have proposed many techniques for representation and analysis of the varying shape of objects, such as active contour (Kass et. al., 1998) and deformable template (Yuille et. al., 1989). However, the active contour, which consists of a set of points, is too flexible to limit its deformation to a reasonable amount of variations for a specific object and it does not have the ability to specify a specific shape. The deformable template, which consists of a set of parametric curves, is difficult to represent all the shape deformations of an object due to 3D rotation or self-deformations because the deformations are too complex to be explained by the combination of hand crafted simple parametric curves.

AN ANALYTICAL SOLUTION TO THE PERSPECTIVE-N-POINT PROBLEM FOR COMMON PLANAR CAMERA AND FOR CATADIOPTRIC SENSOR

2008 ◽  
Vol 08 (01) ◽  
pp. 135-155 ◽  
Author(s):  
JONATHAN FABRIZIO ◽  
JEAN DEVARS
Keyword(s):  
Computer Vision ◽  
Analytical Solution ◽  
Real Time ◽  
Video Camera ◽  
Coordinate Space ◽  
Point Problem ◽  
Localization Accuracy ◽  
Computer Vision Applications ◽  
Set Of Points ◽  
Intrinsic And Extrinsic Parameters

The Perspective-N-Point problem (PNP) is a notable problem in computer vision. It consists of given N points known in an object coordinate space and their projection onto the image, estimating the distance between the video camera and the set of points. By the use of an unusual formulation, we propose a method to get a strictly analytical solution based on the resolution of linear systems. This solution can be computed instantly and is well adapted to real time computer vision applications. Our approach is general enough to work with a nonlinear sensor like a catadioptric panoramic sensor. To improve the localization accuracy, we also provide a technique to correct geometrical distortion. This algorithm also corrects little errors on intrinsic and extrinsic parameters. Well implemented, this correction can be performed in real time.

scholarly journals Smooth determinantal varieties and critical loci in multiview geometry

2021 ◽  
Author(s):  
Marina Bertolini ◽  
Roberto Notari ◽  
Cristina Turrini
Keyword(s):  
Computer Vision ◽  
Reconstruction Problem ◽  
Projective Varieties ◽  
Critical Locus ◽  
Multiview Geometry ◽  
Determinantal Varieties ◽  
Set Of Points

AbstractLinear projections from $$\mathbb {P}^k$$ P k to $$\mathbb {P}^h$$ P h appear in computer vision as models of images of dynamic or segmented scenes. Given multiple projections of the same scene, the identification of sufficiently many correspondences between the images allows, in principle, to reconstruct the position of the projected objects. A critical locus for the reconstruction problem is a variety in $$\mathbb {P}^k$$ P k containing the set of points for which the reconstruction fails. Critical loci turn out to be determinantal varieties. In this paper we determine and classify all the smooth critical loci, showing that they are classical projective varieties.

Influence of site of regional ischemia on LV cavity shape change in dogs

1988 ◽  
Vol 254 (3) ◽  
pp. H547-H557 ◽  
Author(s):  
P. Marino ◽  
D. Kass ◽  
J. Lima ◽  
W. L. Maughan ◽  
W. Graves ◽  
...  
Keyword(s):  
Shape Change ◽  
Left Ventricular ◽  
Acute Ischemia ◽  
Short Axis ◽  
Cavity Shape ◽  
Specific Geometry ◽  
Specific Shape ◽  
Fourier Spectra ◽  
Shape Deformations ◽  
Regional Inhomogeneity

We assessed whether altering the location of acute ischemia produced differing and consistent changes in cavity shape in the canine left ventricle. Twenty anesthetized open-chest dogs underwent transient occlusion of the left anterior descending (LAD) or circumflex (Circ) artery, and cavity shape change was recorded in two-dimensional short-axis echocardiograms. The extent of injury was assessed by radiolabeled microspheres. Shape was analyzed by converting digitized endocardial contours into polar form and expressing the result as a Fourier series. Series terms reflected specific shape deformations, i.e., 2nd term would equal "elongation," 3rd term would equal "triangular." During LAD occlusions, 32.5 +/- 3.0% of the ventricle was hypoperfused compared with 29.8 +/- 2.9% during Circ occlusions (NS). Normal ventricular shape became more circular during ejection indicated by a reduction in the power in nearly all of the Fourier spectra components. During Circ occlusion, the chamber became more elongated, seen in a 63 +/- 16% rise in the 2nd component, and overall shape significantly less circular at end systole than at end diastole. LAD occlusion produced an entirely different pattern, one with no significant elongation but the development of a more triangular shape (86 +/- 27% rise in the 3rd term) by end systole. We conclude that there are characteristic and contrasting shape deformations in LV short-axis contours that depend on the site of ischemic injury. These changes may relate to site-specific geometry and loading, and they point to potential limitations of left ventricular models that do not account for regional inhomogeneity.

scholarly journals All You Need Is Boundary: Toward Arbitrary-Shaped Text Spotting

2020 ◽  
Vol 34 (07) ◽  
pp. 12160-12167 ◽  
Author(s):  
Hao Wang ◽  
Pu Lu ◽  
Hui Zhang ◽  
Mingkun Yang ◽  
Xiang Bai ◽  
...  
Keyword(s):  
Computer Vision ◽  
State Of The Art ◽  
Text Detection ◽  
Text Recognition ◽  
Scene Text Detection ◽  
Scene Text ◽  
End To End ◽  
Text Spotting ◽  
Set Of Points ◽  
Instance Segmentation

Recently, end-to-end text spotting that aims to detect and recognize text from cluttered images simultaneously has received particularly growing interest in computer vision. Different from the existing approaches that formulate text detection as bounding box extraction or instance segmentation, we localize a set of points on the boundary of each text instance. With the representation of such boundary points, we establish a simple yet effective scheme for end-to-end text spotting, which can read the text of arbitrary shapes. Experiments on three challenging datasets, including ICDAR2015, TotalText and COCO-Text demonstrate that the proposed method consistently surpasses the state-of-the-art in both scene text detection and end-to-end text recognition tasks.

scholarly journals Creation and Demonstration of a Framework for Handling Paths in ITK

2005 ◽  
Author(s):  
John Galeotti ◽  
George Stetten
Keyword(s):  
Active Contour ◽  
General Framework ◽  
Dimensional Space ◽  
Data Types ◽  
Parametric Curves ◽  
Chain Codes

A hierarchy of path data types and basic path filters were added to ITK, providing a general framework for curves that map a scalar value to a point in n-dimensional space. The framework supports curves that are either continuous (parametric curves) or discrete (chain-codes). Example usage of the entire framework is demonstrated using a previously published 2D active contour algorithm that was converted to ITK.

scholarly journals Object Tracking based on Fuzzy Color Blobs

2012 ◽  
Vol 22 ◽  
pp. 27-34
Author(s):  
Francisco-Javier Montecillo-Puente ◽  
Victor Ayala-Ramirez
Keyword(s):  
Computer Vision ◽  
Object Tracking ◽  
Object Representation ◽  
Spatial Relationships ◽  
Interest Points ◽  
Articulated Objects ◽  
Specific Object

One of the mayor goals in computer vision is object representation. Object representation aims to determine a set of features that best represents a specific object in an image, for example interest points, edges, color and texture. However, objects are generally composed of several regions containing different information which is more or less convenient to be represented by one of these features. Furthermore, each of these regions could be static or moving with respect to each other. In this sense, this paper presents an object representation based on fuzzy color blobs and spatial relationships among them. This approach of object representation is used to track rigid and articulated objects.

Video Graphics and High-Voltage Electron Microscopy For Analysis of Microtubule Distributions In Fixed Cells

1990 ◽  
Vol 48 (1) ◽  
pp. 524-525
Author(s):  
Richard Mcintosh ◽  
David Mastronarde ◽  
Kent McDonald ◽  
Rubai Ding
Keyword(s):  
Electron Microscopy ◽  
Cross Sections ◽  
Cell Shape ◽  
Video Camera ◽  
Computer Memory ◽  
High Voltage Electron Microscopy ◽  
Thin Sections ◽  
Voltage Electron ◽  
Morphogenetic Event ◽  
Set Of Points

Microtubules (MTs) are cytoplasmic polymers whose dynamics have an influence on cell shape and motility. MTs influence cell behavior both through their growth and disassembly and through the binding of enzymes to their surfaces. In either case, the positions of the MTs change over time as cells grow and develop. We are working on methods to determine where MTs are at different times during either the cell cycle or a morphogenetic event, using thin and thick sections for electron microscopy and computer graphics to model MT distributions.One approach is to track MTs through serial thin sections cut transverse to the MT axis. This work uses a video camera to digitize electron micrographs of cross sections through a MT system and create image files in computer memory. These are aligned and corrected for relative distortions by using the positions of 8 - 10 MTs on adjacent sections to define a general linear transformation that will align and warp adjacent images to an optimum fit. Two hundred MT images are then used to calculate an “average MT”, and this is cross-correlated with each micrograph in the serial set to locate points likely to correspond to MT centers. This set of points is refined through a discriminate analysis that explores each cross correlogram in the neighborhood of every point with a high correlation score.

Human Vision and Computer Vision

1985 ◽  
Vol 30 (1) ◽  
pp. 47-47
Author(s):  
Herman Bouma
Keyword(s):  
Computer Vision ◽  
Human Vision
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