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A Morphable Model For The Synthesis Of 3D Faces

by Volker Blanz , Thomas Vetter , 1999
"... In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can either be generated automatically from one or more photographs, or modeled directly through an intuitive user interface. Users are assisted in two key problems of computer aided face modeling. First, new face i ..."
Abstract - Cited by 1084 (55 self) - Add to MetaCart
In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can either be generated automatically from one or more photographs, or modeled directly through an intuitive user interface. Users are assisted in two key problems of computer aided face modeling. First, new face

Photo tourism: Exploring photo collections in 3D

by Noah Snavely, Steven M. Seitz, Richard Szeliski - In Proc. ACM SIGGRAPH , 2006
"... Figure 1: Our system takes unstructured collections of photographs such as those from online image searches (a) and reconstructs 3D points and viewpoints (b) to enable novel ways of browsing the photos (c). We present a system for interactively browsing and exploring large unstructured collections o ..."
Abstract - Cited by 677 (38 self) - Add to MetaCart
Figure 1: Our system takes unstructured collections of photographs such as those from online image searches (a) and reconstructs 3D points and viewpoints (b) to enable novel ways of browsing the photos (c). We present a system for interactively browsing and exploring large unstructured collections

DART: Directed automated random testing

by Patrice Godefroid, Nils Klarlund, Koushik Sen - In Programming Language Design and Implementation (PLDI , 2005
"... We present a new tool, named DART, for automatically testing software that combines three main techniques: (1) automated extraction of the interface of a program with its external environment using static source-code parsing; (2) automatic generation of a test driver for this interface that performs ..."
Abstract - Cited by 823 (41 self) - Add to MetaCart
that performs random testing to simulate the most general environment the program can operate in; and (3) dynamic analysis of how the program behaves under random testing and automatic generation of new test inputs to direct systematically the execution along alternative program paths. Together, these three

Risk, Return and Equilibrium: Empirical Tests

by Eugene F. Fama, James D. Macbe Th - Journal of Political Economy , 1973
"... Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at ..."
Abstract - Cited by 1445 (10 self) - Add to MetaCart
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at

Cointegration and Tests of Present Value Models

by John Y. Campbell, Robert J. Shiller , 1986
"... ..."
Abstract - Cited by 525 (9 self) - Add to MetaCart
Abstract not found

Efficient tests for an autoregression unit root

by Graham Elliott, Thomas J. Rothenberg, James H. Stock - ECONOMETRICA , 1996
"... ..."
Abstract - Cited by 648 (4 self) - Add to MetaCart
Abstract not found

Face Recognition Based on Fitting a 3D Morphable Model

by Volker Blanz, Thomas Vetter - IEEE Trans. Pattern Anal. Mach. Intell , 2003
"... Abstract—This paper presents a method for face recognition across variations in pose, ranging from frontal to profile views, and across a wide range of illuminations, including cast shadows and specular reflections. To account for these variations, the algorithm simulates the process of image format ..."
Abstract - Cited by 546 (19 self) - Add to MetaCart
formation in 3D space, using computer graphics, and it estimates 3D shape and texture of faces from single images. The estimate is achieved by fitting a statistical, morphable model of 3D faces to images. The model is learned from a set of textured 3D scans of heads. We describe the construction

Using spin images for efficient object recognition in cluttered 3D scenes

by Andrew E. Johnson, Martial Hebert - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1999
"... We present a 3-D shape-based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion. Recognition is based on matching surfaces by matching points using the spin-image representation. The spin-image is a data level shape descriptor that i ..."
Abstract - Cited by 571 (9 self) - Add to MetaCart
We present a 3-D shape-based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion. Recognition is based on matching surfaces by matching points using the spin-image representation. The spin-image is a data level shape descriptor

Property Testing and its connection to Learning and Approximation

by Oded Goldreich, Shafi Goldwasser, Dana Ron
"... We study the question of determining whether an unknown function has a particular property or is ffl-far from any function with that property. A property testing algorithm is given a sample of the value of the function on instances drawn according to some distribution, and possibly may query the fun ..."
Abstract - Cited by 498 (68 self) - Add to MetaCart
We study the question of determining whether an unknown function has a particular property or is ffl-far from any function with that property. A property testing algorithm is given a sample of the value of the function on instances drawn according to some distribution, and possibly may query

Lag length selection and the construction of unit root tests with good size and power

by Serena Ng, Pierre Perron - Econometrica , 2001
"... It is widely known that when there are errors with a moving-average root close to −1, a high order augmented autoregression is necessary for unit root tests to have good size, but that information criteria such as the AIC and the BIC tend to select a truncation lag (k) that is very small. We conside ..."
Abstract - Cited by 534 (14 self) - Add to MetaCart
It is widely known that when there are errors with a moving-average root close to −1, a high order augmented autoregression is necessary for unit root tests to have good size, but that information criteria such as the AIC and the BIC tend to select a truncation lag (k) that is very small. We
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