Search Results for author:
Found 54 papers, 4 papers with code
Socially Pertinent Robots in Gerontological Healthcare
Despite the many recent achievements in developing and deploying social robotics, there are still many underexplored environments and applications for which systematic evaluation of such systems by end-users is necessary.
Visually Guided Object Grasping
In this paper we present a visual servoing approach to the problem of object grasping and more generally, to the problem of aligning an end-effector with an object.
Polyhedral Object Recognition by Indexing
In this paper we address the problem of recognizing 3-D polyhedral objects from 2-D images by indexing.
Hand-Eye Calibration
In the light of this comparison, the non-linear optimization method, that solves for rotation and translation simultaneously, seems to be the most robust one with respect to noise and to measurement errors.
Robot Hand-Eye Calibration using Structure-from-Motion
In this paper we propose a new flexible method for hand-eye calibration.
Expression-preserving face frontalization improves visually assisted speech processing
The method alternates between the estimation of (i)~the rigid transformation (scale, rotation, and translation) and (ii)~the non-rigid deformation between an arbitrarily-viewed face and a face model.
The impact of removing head movements on audio-visual speech enhancement
This paper investigates the impact of head movements on audio-visual speech enhancement (AVSE).
High-Resolution Depth Maps Based on TOF-Stereo Fusion
Most of these systems suffer from the problems of noise in the range-data and resolution mismatch between the range sensor and the color cameras, since the resolution of current range sensors is much less than the resolution of color cameras.
3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching
We discuss solutions for the exact and inexact graph isomorphism problems and recall the main spectral properties of the combinatorial graph Laplacian; We provide a novel analysis of the commute-time embedding that allows us to interpret the latter in terms of the PCA of a graph, and to select the appropriate dimension of the associated embedded metric space; We derive a unit hyper-sphere normalization for the commute-time embedding that allows us to register two shapes with different samplings; We propose a novel method to find the eigenvalue-eigenvector ordering and the eigenvector signs using the eigensignature (histogram) which is invariant to the isometric shape deformations and fits well in the spectral graph matching framework, and we present a probabilistic shape matching formulation using an expectation maximization point registration algorithm which alternates between aligning the eigenbases and finding a vertex-to-vertex assignment.
Robust Factorization Methods Using a Gaussian/Uniform Mixture Model
In this paper we address the problem of building a class of robust factorization algorithms that solve for the shape and motion parameters with both affine (weak perspective) and perspective camera models.
Articulated Shape Matching Using Laplacian Eigenfunctions and Unsupervised Point Registration
Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph.
Fusion of Range and Stereo Data for High-Resolution Scene-Modeling
The accuracy of the method is not compromised, owing to three properties of the data-term in the energy function.
An Overview of Depth Cameras and Range Scanners Based on Time-of-Flight Technologies
Time-of-flight (TOF) cameras are sensors that can measure the depths of scene-points, by illuminating the scene with a controlled laser or LED source, and then analyzing the reflected light.
Cyclopean Geometry of Binocular Vision
The recovery of visual direction and depth from retinal images is discussed, with reference to the relevant psychophysical and neurophysiological literature.
Image Matching with Scale Adjustment
In this paper we address the problem of matching two images with two different resolutions: a high-resolution image and a low-resolution one.
Topology-Adaptive Mesh Deformation for Surface Evolution, Morphing, and Multi-View Reconstruction
However, explicit mesh representations, while allowing for accurate surface modelling, suffer from the inherent difficulty of reliably dealing with self-intersections and topological changes such as merges and splits.
Rigid and Articulated Point Registration with Expectation Conditional Maximization
This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration.
A Differential Model of the Complex Cell
Gabor functions can also be combined in an `energy model' of the complex cell response.
Conjugate Mixture Models for Clustering Multimodal Data
The algorithm and its variants are tested and evaluated within the task of 3D localization of several speakers using both auditory and visual data.
Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals
We address the problem of human motion tracking by registering a surface to 3-D data.
FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement
In our proposed FullSubNet, we connect a pure full-band model and a pure sub-band model sequentially and use practical joint training to integrate these two types of models' advantages.
Face Frontalization Based on Robustly Fitting a Deformable Shape Model to 3D Landmarks
We propose to model inliers and outliers with the generalized Student's t-probability distribution function, a heavy-tailed distribution that is immune to non-Gaussian errors in the data.
Learning Visual Voice Activity Detection with an Automatically Annotated Dataset
Visual voice activity detection (V-VAD) uses visual features to predict whether a person is speaking or not.
Variational Inference and Learning of Piecewise-linear Dynamical Systems
In this paper, we propose a variational approximation of piecewise linear dynamical systems.
Unsupervised Performance Analysis of 3D Face Alignment with a Statistically Robust Confidence Test
The results show that the proposed analysis is consistent with supervised metrics and that it can be used to measure the accuracy of both predicted landmarks and of automatically annotated 3DFA datasets, to detect errors and to eliminate them.
A Recurrent Variational Autoencoder for Speech Enhancement
This paper presents a generative approach to speech enhancement based on a recurrent variational autoencoder (RVAE).
Audio-visual Speech Enhancement Using Conditional Variational Auto-Encoders
Variational auto-encoders (VAEs) are deep generative latent variable models that can be used for learning the distribution of complex data.
How To Train Your Deep Multi-Object Tracker
In this paper, we bridge this gap by proposing a differentiable proxy of MOTA and MOTP, which we combine in a loss function suitable for end-to-end training of deep multi-object trackers.
Ranked #4 on
Multi-Object Tracking
on 2D MOT 2015
CANU-ReID: A Conditional Adversarial Network for Unsupervised person Re-IDentification
Unsupervised person re-ID is the task of identifying people on a target data set for which the ID labels are unavailable during training.
Extended Gaze Following: Detecting Objects in Videos Beyond the Camera Field of View
In this paper we address the problems of detecting objects of interest in a video and of estimating their locations, solely from the gaze directions of people present in the video.
Speech enhancement with variational autoencoders and alpha-stable distributions
This paper focuses on single-channel semi-supervised speech enhancement.
A variance modeling framework based on variational autoencoders for speech enhancement
In this paper we address the problem of enhancing speech signals in noisy mixtures using a source separation approach.
Semi-supervised multichannel speech enhancement with variational autoencoders and non-negative matrix factorization
In this paper we address speaker-independent multichannel speech enhancement in unknown noisy environments.
Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers
We propose a variational inference model which amounts to approximate the joint distribution with a factorized distribution.
DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture Model
In this paper, we address the problem of how to robustly train a ConvNet for regression, or deep robust regression.
A Comprehensive Analysis of Deep Regression
Deep learning revolutionized data science, and recently its popularity has grown exponentially, as did the amount of papers employing deep networks.
Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction
Our approach enables a robot to learn and to adapt its gaze control strategy for human-robot interaction neither with the use of external sensors nor with human supervision.
Plane-extraction from depth-data using a Gaussian mixture regression model
We propose a novel algorithm for unsupervised extraction of piecewise planar models from depth-data.
Deep Mixture of Linear Inverse Regressions Applied to Head-Pose Estimation
In this particular problem, we show that inverse regression outperforms regression models currently used by state-of-the-art computer vision methods.
Tracking Gaze and Visual Focus of Attention of People Involved in Social Interaction
The visual focus of attention (VFOA) has been recognized as a prominent conversational cue.
Joint Alignment of Multiple Point Sets with Batch and Incremental Expectation-Maximization
Solutions to this problem are often approximated by repeatedly solving for pairwise registration, which results in an uneven treatment of the sets forming a pair: a model set and a data set.
Audio-Visual Speaker Diarization Based on Spatiotemporal Bayesian Fusion
An audio-visual spatiotemporal diarization model is proposed.
Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions
Head-pose estimation has many applications, such as social event analysis, human-robot and human-computer interaction, driving assistance, and so forth.
An On-line Variational Bayesian Model for Multi-Person Tracking from Cluttered Scenes
In this paper, we propose an on-line variational Bayesian model for multi-person tracking from cluttered visual observations provided by person detectors.
EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis
We propose a model selection method based on a minimum message length criterion, provide a weight initialization strategy, and validate the proposed algorithms by comparing them with several state of the art parametric and non-parametric clustering techniques.
Hyper-Spectral Image Analysis with Partially-Latent Regression and Spatial Markov Dependencies
This involves resolving inverse problems which can be addressed within machine learning, with the advantage that, once a relationship between physical parameters and spectra has been established in a data-driven fashion, the learned relationship can be used to estimate physical parameters for new hyper-spectral observations.
Skeletal quads: Human action recognition using joint quadruples
Further, the use of a Fisher kernel representation is suggested to describe the skeletal quads contained in a (sub)action.
Ranked #120 on
Skeleton Based Action Recognition
on NTU RGB+D
Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression
Indeed, we demonstrate that the method can be used for audio-visual fusion, namely to map speech signals onto images and hence to spatially align the audio and visual modalities, thus enabling to discriminate between speaking and non-speaking faces.
Continuous Action Recognition Based on Sequence Alignment
Continuous action recognition is more challenging than isolated recognition because classification and segmentation must be simultaneously carried out.
Robust Temporally Coherent Laplacian Protrusion Segmentation of 3D Articulated Bodies
In an unsupervised context, i. e., no prior model of the moving object(s) is available, such a structure has to be learned from the data in a bottom-up fashion.
Cross-calibration of Time-of-flight and Colour Cameras
It is desirable to merge the depth and colour information, in order to obtain a coherent scene representation.
Automatic Detection of Calibration Grids in Time-of-Flight Images
It is convenient to calibrate time-of-flight cameras by established methods, using images of a chequerboard pattern.
Vision-Guided Robot Hearing
Natural human-robot interaction in complex and unpredictable environments is one of the main research lines in robotics.
High-Dimensional Regression with Gaussian Mixtures and Partially-Latent Response Variables
We introduce a mixture of locally-linear probabilistic mapping model that starts with estimating the parameters of inverse regression, and follows with inferring closed-form solutions for the forward parameters of the high-dimensional regression problem of interest.
