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The Menpo project

The Menpo project The Menpo Project The Menpo Project Overview . The Menpo Project [1] is a BSD-licensed set of tools and software designed to provide an end-to-end pipeline for collection and annotation of image and 3D mesh data. In particular, the Menpo Project provides tools for annotating images and meshes with a sparse set of fiducial markers that we refer to as landmarks. For example, Figure 1 shows an example of a face image that has been annotated with 68 2D landmarks. These landmarks are useful in a variety of areas in Computer Vision and Machine Learning including object detection, deformable modelling and tracking. The Menpo Project aims to enable researchers, practitioners and students to easily annotate new data sources and to investigate existing datasets. Of most interest to the Computer Vision is the fact that The Menpo Project contains completely open source implementations of a number of state-of-the-art algorithms for face detection and deformable model building. In the Menpo Project, we are actively developing and contributing to the state-of-the-art in deformable modelling [2], [3], [4], [5]. Characteristic examples of widely used state-of-the-art deformable model algorithms are Active Appearance Models [6],[7], Constrained Local Models [8], [9] and Supervised Descent Method http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGMultimedia Records Association for Computing Machinery

The Menpo project

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2016 by ACM Inc.
ISSN
1947-4598
DOI
10.1145/2982857.2982858
Publisher site
See Article on Publisher Site

Abstract

The Menpo Project The Menpo Project Overview . The Menpo Project [1] is a BSD-licensed set of tools and software designed to provide an end-to-end pipeline for collection and annotation of image and 3D mesh data. In particular, the Menpo Project provides tools for annotating images and meshes with a sparse set of fiducial markers that we refer to as landmarks. For example, Figure 1 shows an example of a face image that has been annotated with 68 2D landmarks. These landmarks are useful in a variety of areas in Computer Vision and Machine Learning including object detection, deformable modelling and tracking. The Menpo Project aims to enable researchers, practitioners and students to easily annotate new data sources and to investigate existing datasets. Of most interest to the Computer Vision is the fact that The Menpo Project contains completely open source implementations of a number of state-of-the-art algorithms for face detection and deformable model building. In the Menpo Project, we are actively developing and contributing to the state-of-the-art in deformable modelling [2], [3], [4], [5]. Characteristic examples of widely used state-of-the-art deformable model algorithms are Active Appearance Models [6],[7], Constrained Local Models [8], [9] and Supervised Descent Method

Journal

ACM SIGMultimedia Records – Association for Computing Machinery

Published: Aug 2, 2016

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