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2D/3D Face Recognition

In this project, started in collaboration with the IRIS Computer Vision lab, University of Southern California, we address the problem of 2D/3D face recognition with a gallery containing 3D models of enrolled subjects and a probe set composed by only 2D imagery with pose variations. Raw 3D models are present in the gallery for each person, where each 3D model shows both a facial shape as a 3D mesh and a 2D component as a texture registered with the shape; by the other hand it is assumed to have only 2D images in the probe set.

Facial shape as a 3D mesh and a 2D component as a texture registered with the shape

This scenario, defined as is, is an ill-posed problem considering the gap between the kind of information present in the gallery and the one available in the probe.

In experimental result we evaluate the reconstruction result about the 3D shape estimation from multiple 2D images and the face recognition pipeline implemented considering a range of facial poses in the probe set, up to ±45 degrees.

Future directions can be found by investigating a method that is able to fuse the 3D face modeling with the face recognition technique developed accounting for pose variations.

Recognition results

Results: baseline vs. our approach

This worked was conducted by Iacopo Masi during his internship in 2012/2013at the IRIS Computer Vision lab, University of Southern California.

USC University of Southern California

An article about MICC on “Il Sole 24 Ore”

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On Monday, May 13 an article about the Media Integration and Communication, Center, entitled “Comunicazione multimediale al top. Tra le iniziative, il Centro di Competenza su Nuovi Media per Beni Culturali”, was published in the Special Computing, ICT and Telecommunications Magazine of Il Sole 24 Ore dedicated to Research and Technological Innovation. The article is available only in italian.

Il Sole 24 Ore – Speciale Eventi

NEMECH center opening

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The New Media for Cultural Heritage (NEMECH) Competence Center is an organization structure for carrying out transfer of research know-how developed in the laboratories of the University of Florence.

Its brand-new center opens the doors to the public on Friday 15th of March 2013, at the EUROCITIES CULTURE FORUM, in order to show activities and work-in-progress projects in the filed of Cultural Heritage.

NEMECH center @ MURATE Urban Park of Innovation

People will be invited to visit the new spaces of the center and to experience some live demos about Natural Interaction for Cultural Heritage, Computer Vision behaviour analysis, augmented reality through mobile systems, user profiling and recommendation, new social media and social networks analysis.

In particular, there will be installations about the following projects:

MICC staff will be available to answer any questions and to explain all the projects in which NEMECH is currently involved.

We will be pleased to welcome you from 11 a.m. to 2 p.m at Piazza della Neve, inside the MURATE Urban Park of Innovation of Florence.

Simone Ercoli

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Simone Ercoli was born on 18 May 1983 in Siena. He received a Master’s Degree in computer engineering from University of Florence in 2012 with a thesis on “Design and Development of an Augmented Reality Application for mobile systems” . He’s a PhD Candidate and currently working as researcher in the Visual Information and Media Lab at the Media Integration and Communication Center, University of Florence.

Simone Ercoli

Dario Di Fina

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Dario Di Fina was born on 12 October 1986 in Palermo. He received his Master’s Degree cum laude in computer engineering from the University of Florence, in 2012 with his thesis “Multi-Target Data Association by Sparse Reconstruction”.

He is currently a PhD Candidate at the Visual Information and Media Lab under the supervision of Prof. Alberto Del Bimbo, working with Giuseppe Lisanti, Ph.D., Svebor Karaman, PhD and Andrew D. Bagdanov, Ph.D. in the Media Integration and Communication Center, University of Florence.
His main research interests are focused on the application of pattern recognition and computer vision specifically in the field of gaze estimation, multi-characteristic face classification, human behaviour and multi-target tracking.

Dario Di Fina

RIMSI: Integrated Research of Simulation Models

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The RIMSI project, funded by Regione Toscana, includes study, experimentation and development of a protocol for the validation of procedures and implementation of a prototype multimedia software system to improve protocols and training in emergency medicine through the use of interactive simulation techniques.

RIMSI – patient rianimation scene

Medical simulation software currently on the market can play very simple scenarios (one patient) and an equally limited number of actors involved (usually only one doctor and a nurse). In addition, “high-fidelity” simulation scenarios available are almost exclusively limited to the cardio-pulmonary resuscitation and emergency anesthesia. Finally, the user can impersonate a single role (doctor or nurse) while the other operator actions are controlled by the computer.

To overcome these important limitations of the programs currently available on the market, it is proposed the creation of a software capable of reproducing realistic scenarios (the inside of an emergency room, the scene of a car accident, etc. ..) with both single mode -user (the user controls the function of a single operator while the computer controls the other presonages) and multi-user (each user controls one of the actors in the scenario).

Our proposal is to develop a multi-user application that allows useres to interact both via mouse & keyboard and with body gestures. For this purpose we are currently developing a 3D trainig scenario in which learners would be able to interact through a Microsoft Kinect.

This work in progress will be presented during the Workshop on User Experience in e-Learning and Augmented Technologies in Education (UXeLATE) – ACM Multimedia, that will be held in Nara, Japan.

We organize ECCV 2012

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The Media Integration and Communication Center organizes ECCV 2012, the 12th European Conference on Computer Vision.

12th European Conference on Computer Vision

The European Conference on Computer Vision is one of the top international conferences on computer vision research. ECCV 2012 solicits submissions for papers that describe scientific achievements and long term research challenges, point to new research directions, or provide new insights or brave perspectives that pave the way to innovation. Subjects of interest are computer vision and aspects of related disciplines (such as machine learning, computer graphics, biological vision, mathematics) which illuminate the state of the art in computer vision. Accepted papers will be presented in the oral and poster sessions of the ECCV 2012 technical program. Continuing the top quality tradition of ECCVs, it will be a single-track conference with double-blind peer review process.

FaceHugger: The ALIEN Tracker Applied to Faces

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The ALIEN visual tracker is a generic visual object tracker achieving state of the art performance. The object is selected at run-time by drawing a bounding box around it and then its appearance is learned and tracked as time progresses.

The ALIEN tracker has been shown to outperform other competitive trackers, especially in the case of long-term tracking, large amount of camera blur, low frame rate videos and severe occlusions including full object disappearance.

The scientific paper introducing the technology behind the tracker will appear at the 12th European Conference in Computer Vision 2012 (eccv2012) under the following title: FaceHugger: The ALIEN Tracker Applied to Faces. In Proceedings of European Conference on Computer Vision (ECCV) – DEMO Session – 2012 Florence Italy.

A real time demo of the released application will also be given during the conference.

Application Demo: here we are releasing the real-time demo software that will be presented and demonstrated at the conference. Currently the software is only working under Microsoft Windows 64bit. The released software demo has been developed using OpenCV and Matlab and deployed as a self installing package. The self-installer will install the MCR (Matlab Compiler Runtime) and will copy some OpenCV .dll files and the application executable.

Note: There is no need to install OpenCV or Matlab, the self-installing package will provide all the necessary files to run the tracker as a standalone application.

[Download not found]

Installation:

Double click on the exe-file AlienTracker_pkg.exe. The command window will appear, and the exe-file will inflate the files contained in the same directory where you have downloaded AlienTracker_pkg.exe. The MCR (Matlab Compiler Runtime) installation wizard will start with the language window.
Once the MCR installation is completed double click on the AlienTracker.exe. It might take some time (i.e. 4/5 seconds) before the execution actually starts.
Select using the mouse the object area that has to be tracked and then press enter.

How to get the best performance: try to avoid including object background inside the selected bounding box:

FaceHugger: how to get the best performance step 1

It is not important to include the whole object; some parts may be left out of the bounding box:

FaceHugger: how to get the best performance step 2

Provide a reasonable sized bounding box. Small bounding boxes do not provide the necessary visual information to achieve good tracking:

FaceHugger: how to get the best performance step 3

Current release limits:

Only Windows 7 64bit platforms supported.
Application only supports the first installed webcam device.
Image resolution is resized at 320×240.
Videos cannot be processed.
The tracked trajectory data cannot be exported.
Application interface is very basic.
Only SIFT features are current available. More recent and faster features may be used (SURF, BRIEF, BRISK etc.).

Future release will correct these limitations. Feel free to provide feedback or ask any question by email or social media: pernici@dsi.unifi.it, http://www.youtube.com/user/pernixVision,
https://twitter.com/pernixxx, http://www.facebook.com/federico.pernici.

Federico Pernici will present FaceHugger: Alien tracker at ECCV2012

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Federico Pernici

A real time demo of the released application will also be given during the conference. Read more

Game Theory in Pattern Recognition and Machine Learning

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The development of game theory in the early 1940’s by John von Neumann was a reaction against the then dominant view that problems in economic theory can be formulated using standard methods from optimization theory. Indeed, most real – world economic problems typically involve conflicting interactions among decision-making agents that cannot be adequately captured by a single (global) objective function, thereby requiring a different, more sophisticated treatment. Accordingly, the main point made by game theorists is to shift the emphasis from optimality criteria to equilibrium conditions.

Game Theory in Pattern Recognition and Machine Learning: graph transduction

As it provides an abstract theoretically-founded framework to elegantly model complex scenarios, game theory has found a variety of applications not only in economics and, more generally, social sciences but also in different fields of engineering and information technologies. In particular, in the past there have been various attempts aimed at formulating problems in computer vision, pattern recognition and machine learning from a game-theoretic perspective and, with the recent development of algorithmic game theory, the interest in these communities around game-theoretic models and algorithms is growing at a fast pace.

The goal of these three lectures is to offer an introduction to the basic concepts of game theory and to provide an overview of the work we’re currently doing in my group on the use of game-theoretic models in pattern recognition, computer vision, and machine learning.

I shall assume no pre-existing knowledge of game theory by the audience, thereby making the lectures self-contained and understandable by a non-expert.

The three lectures will be structured as follows:

Lecture 1: Introduction to the basic concepts of game theory
Lecture 2: Evolutionary games and data clustering
Lecture 3: Contextual pattern recognition and graph transduction

The lectures are based on two (broader) tutorials I gave at ICPR 2010 and CVPR 2011 (with A. Torsello).