Jean-Philippe Thiran

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Cross-domain synthesizing realistic faces to learn deep models has attracted increasing attention for facial expression analysis as it helps to improve the performance of expression recognition accuracy despite having small number of real training images. ...

The theory of compressed sensing (CS) leverages upon structure of signals in order to reduce the number of samples needed to reconstruct a signal, compared to the Nyquist rate. Although CS approaches have been proposed for ultrasound (US) imaging with promising results, practical implementations are hard to achieve due to the impossibility to mimic random sampling on a US probe and to the high memory requirements of the measurement model. In this paper, we propose a CS framework for US imaging based on an e

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, ...

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To m ...

Existing reference (RF)-based super-resolution (SR) models try to improve perceptual quality in SR under the assumption of the availability of high-resolution RF images paired with low-resolution (LR) inputs at testing. As the RF images should be similar i ...

We present a method for face detection which uses a new SVM structure trained in an expert manner in the eigenface space. This robust method has been introduced as a post processing step in a realtime face detection system. The principle is to train several parallel SVMs on subsets of some initial training set and then train a second layer SVM on the margins of the first layer of SVMs. This approach presents a number of advantages over the classical SVM: firstly the training time is considerably reduced and

Purpose To obtain whole-brain high-resolution T-2 maps in 2 minutes by combining simultaneous multislice excitation and low-power PINS (power independent of number of slices) refocusing pulses with undersampling and a model-based reconstruction. Methods A ...

This document presents a brief description of the Medical Image Processing (MIP) library developed by the Brain Group of the Signal Processing Institute (ITS) at Swiss Federal Institute of Technology (EPFL). This library is a result of more than three years of research by Meritxell Bach Cuadra, Torsten Butz, Eduardo Solanas and Olivier Cuisenare, carried out under the supervision of Jean-Philippe Thiran. You can find more detailed information about the library at our web page located at http://ltswww.epfl.c

In this paper, we address the problem of finding image decompositions that allow good compression performance, and that are also efficient for face authentication. We propose to decompose the face image using Matching Pursuit and to perform the face authentication in the compressed domain using a MLP (Multi-Layer Perceptron) classifier. We provide experimental results and comparisons with PCA and LDA systems on the multi-modal benchmark database BANCA using its associated protocol.

Inferring microscopic tissue properties from the measured signal is one of the main objectives of diffusion-weighted magnetic resonance imaging. The use of Monte-Carlo Simulations for DW-MRI on realistic substrates will help the study of DWI-MRI signals in controlled environments and investigate, extract, and validate approaches for the understanding of white matter features. This work provides a unique framework for building complex white matter phantoms with novel properties, such as 1) substrates with a

The problem of feature selection has been thoroughly analyzed in the context of pattern classification, with the purpose of avoiding the curse of dimensionality. However, in the context of multimodal signal processing, this problem has been studied less. O ...

This paper addresses the problem of automatic facial expression recognition in videos, where the goal is to predict discrete emotion labels best describing the emotions expressed in short video clips. Building on a pre-trained convolutional neural network ...

Quantitative MRI allows the characterization and comparison of microstructural tissue properties and, by defining normative ranges for healthy tissue, detection of pathology. The simultaneous evaluation of multiple qMRI measures facilitates the understanding of what biological mechanisms underlie the observed deviations in relaxometry. Here, we introduce the ratio between quantitative T2 and T1 maps (T2/T1) as a microstructural property whose deviations from normative values could be predictive or character

In this paper, we present a 3D geometric flow designed to segment the main core of fiber tracts in diffusion tensor magnetic resonance images. The fundamental assumption of our fiber segmentation technique is that adjacent voxels in a tract have similar pr ...

Ultrafast ultrasound (US) imaging based on plane wave (PW) insonification is a widely used modality nowadays. Two main types of approaches have been proposed for image reconstruction either based on classical delay-and-sum (DAS) or on Fourier reconstructio ...

Cross-ratio (CR)-based eye tracking has been attracting much interest due to its simple setup, yet its accuracy is lower than that of the model-based approaches. In order to improve the estimation accuracy, a multi-camera setup can be exploited rather than ...

When many (m) null hypotheses are tested with a single dataset, the control of the number of false rejections is often the principal consideration. Two popular controlling rates are the probability of making at least one false discovery (FWER) and the expected fraction of false discoveries among all rejections (FDR). Scaled multiple comparison error rates form a new family that bridges the gap between these two extremes. For example, the Scaled Expected Value (SEV) limits the number of false positives relat

In this paper we propose two alternatives to overcome the natural asynchrony of modalities in Audio-Visual Speech Recognition. We first investigate the use of asynchronous statistical models based on Dynamic Bayesian Networks with different levels of async ...

In this paper we propose a method for the automatic counting of pedestrians in video sequences for (automatic) video surveillance applications. We analyse the trajectory data set provided by a detection/tracking system. When using classical target detection and tracking systems, it is well known that the number of detected targets is overestimated/ underestimated. A better representation for the trajectories is given in the ICA (Independent Component Analysis) transformed domain and clustering techniques ar

Microstructure imaging with diffusion MRI (dMRI) is usually based on fitting models to the data using voxelwise nonlinear procedures that (i) are time consuming and (ii) need long acquisitions. Recently, we introduced the AMICO framework to accelerate the ...

Jean-Philippe Thiran

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Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Automatic Mallampati Classification Using Active Appearance Models

A multi-center study: Intra-scan and inter-scan variability of Diffusion Spectrum Imaging

Test-Time Adaptation for Super-Resolution: You Only Need to Overfit on a Few More Images

Face Class Modeling Using Mixture of SVMs

Fast model-based T-2 mapping using SAR-reduced simultaneous multislice excitation

MIP: The ITS-EPFL Medical Image Processing Library

Face Authentication using Client-specific Matching Pursuit

A step forward to improve large numerical phantoms at the microstructure level using CACTUS

Information theoretic feature extraction for audio-visual speech recognition

G2-VER: Geometry Guided Model Ensemble for Video-based Facial Expression Recognition

Normative brain atlas of T2/T1 relaxometry ratio for detection of microstructural pathology

White matter fiber tract segmentation in DT-MRI using geometric flows

Sparse regularization methods in ultrafast ultrasound imaging

Estimating Fusion Weights of a Multi-Camera Eye Tracking System by Leveraging User Calibration Data

Optimality in multiple comparison procedures

Overcoming Asynchrony in Audio-Visual Speech Recognition

Trajectories clustering in ICA space: an application to automatic counting of pedestrians in video sequences

Reducing acquisition time for microstructure imaging with spatially-regularized global optimization