Publications de Jean-Marc Odobez

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Convolutional Neural Networks (CNN) are the leading models for human body landmark detection from RGB vision data. However, as such models require high computational load, an alternative is to rely on depth images which, due to their more simple nature, ca ...

We present an efficient and accurate people detection approach based on deep learning to detect people attacks and intrusion in video surveillance scenarios Unlike other approaches using background segmentation and pre-processing techniques, which are not ...

This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns called motifs from documents given as word×time count matrices (e.g., videos). In this model, documents are represented as a mixture of sequenti ...

This paper addresses the significant challenge of recognizing behaviors in non-human primates, specifically focusing on chimpanzees. Automated behavior recognition is crucial for both conservation efforts and the advancement of behavioral research. However ...

This paper addresses the issue of segmentation and recognition of text embedded in video sequences from their associated text image sequence extracted by a text detection module. To this end, we propose a probabilistic algorithm based on Bayesian adaptive ...

We address the problem of recognizing the visual focus of attention (VFOA) of meeting participants based on their head pose. To this end, the head pose observations are modeled using a Gaussian Mixture Model (GMM) or a Hidden Markov Model (HMM) whose hidde ...

This paper presents a novel approach for visual scene modeling and classification, investigating the combined use of text modeling methods and local invariant features. Our work attempts to elucidate (1) whether a text-like \emph{bag-of-visterms} represent ...

We address the problem of 3D gaze estimation within a 3D environment from remote sensors, which is highly valuable for applications in human-human and human-robot interactions. To the contrary of most previous works, which are limited to screen gazing appl ...

We present a fast method to detect humans from stationary surveillance videos. It is based on a cascade of LogitBoost classifiers which use covariance matrices as object descriptors. We have made several contributions. First, our method learns the correlat ...

Tracking speakers in multiparty conversations constitutes a fundamental task for automatic meeting analysis. In this paper, we present a probabilistic approach to jointly track the location and speaking activity of multiple speakers in a multisensor meetin ...

Visual Focus of Attention (VFOA) estimation in conversation is challenging as it relies on difficult to estimate information (gaze) combined with scene features like target positions and other contextual information (speaking status) allowing to disambigua ...

Gaze estimation is a difficult task, even for humans. However, as humans, we are good at understanding a situation and exploiting it to guess the expected visual focus of attention of people, and we usually use this information to retrieve people's gaze. I ...

To improve visual tracking, a large number of papers study more powerful features, or better cue fusion mechanisms, such as adaptation or contextual models. A complementary approach consists of improving the track management, that is, deciding when to add ...

Bag-of-visual-words or bag-of-visterms (bov) is a common technique used to index Multimedia information with the purposes of retrieval and classification. In this work we address the problem of constructing efficient bov representations of complex shapes a ...

Although automatic gaze estimation is very important to a large variety of application areas, it is difficult to train accurate and robust gaze models, in great part due to the difficulty in collecting large and diverse data (annotating 3D gaze is expensiv ...

Head pose estimation is a fundamental task for face and social related research. Although 3D morphable model (3DMM) based methods relying on depth information usually achieve accurate results, they usually require frontal or mid-profile poses which preclud ...

Learning a discriminative voice embedding allows speaker turns to be compared directly and efficiently, which is crucial for tasks such as diarization and verification. This paper investigates several transfer learning approaches to improve a voice embeddi ...

Predicting where a person is looking is a complex task, requiring to understand not only the person's gaze and scene content, but also the 3D scene structure and the person's situation (are they manipulating? interacting or observing others? attentive?) to ...

Shape representations are critical for visual analysis of cultural heritage materials. This article studies two types of shape representations in a bag-of-words-based pipeline to recognize Maya glyphs. The first is a knowledge-driven Histogram of Orientati ...

As an indicator of attention, gaze is an important cue for human behavior and social interaction analysis. Recent deep learning methods for gaze estimation rely on plain regression of the gaze from images without accounting for potential mismatches in eye ...

Jean-Marc Odobez

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Investigating Depth Domain Adaptation for Efficient Human Pose Estimation

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

A Sequential Topic Model for Mining Recurrent Activities from Long Term Video Logs

From Forest to Zoo: Great Ape Behavior Recognition with Chimpbehave

Video Text Recognition using Sequential Monte Carlo and Error Voting Methods

Recognizing Human Visual Focus of Attention from Head Pose in Meetings

A Thousand Words in a Scene

Gaze Estimation in the 3D Space Using RGB-D Sensors

Fast human detection from joint appearance and foreground feature subset covariances

Audio-visual probabilistic tracking of multiple speakers in meetings

Visual Focus of Attention Estimation in 3D Scene with an Arbitrary Number of Targets

Robust Unsupervised Gaze Calibration Using Conversation and Manipulation Attention Priors

A Track Creation and Deletion Framework for Long-Term Online Multi-Face Tracking

Assessing Sparse Coding Methods for Contextual Shape Indexing of Maya Hieroglyphs

Unsupervised Representation Learning for Gaze Estimation

HeadFusion: 360 degrees Head Pose Tracking Combining 3D Morphable Model and 3D Reconstruction

Improving speech embedding using crossmodal transfer learning with audio-visual data

A Modular Multimodal Architecture for Gaze Target Prediction: Application to Privacy-Sensitive Settings

Evaluating Shape Representations for Maya Glyph Classification

Deep Multitask Gaze Estimation with a Constrained Landmark-Gaze Model