• Publications
  • Influence
Robust Multiresolution Estimation of Parametric Motion Models
TLDR
Numerical results support this approach, as validated by the use of these algorithms on complex sequences, and two robust estimators in a multi-resolution framework are developed.
EYEDIAP: a database for the development and evaluation of gaze estimation algorithms from RGB and RGB-D cameras
TLDR
This paper intends to overcome the lack of a common benchmark for the evaluation of the gaze estimation task from RGB and RGB-D data by introducing a novel database along with a common framework for the training and evaluation of gaze estimation approaches.
Modeling scenes with local descriptors and latent aspects
TLDR
Probabilistic latent semantic analysis generates a compact scene representation, discriminative for accurate classification, and significantly more robust when less training data are available, and the ability of PLSA to automatically extract visually meaningful aspects is exploited to propose new algorithms for aspect-based image ranking and context-sensitive image segmentation.
Multi-Layer Background Subtraction Based on Color and Texture
  • Jian Yao, J. Odobez
  • Computer Science
    IEEE Conference on Computer Vision and Pattern…
  • 17 June 2007
TLDR
A robust multi-layer background subtraction technique which takes advantages of local texture features represented by local binary patterns (LBP) and photometric invariant color measurements in RGB color space and allows to implicitly smooth detection results over regions of similar intensity and preserve object boundaries.
We are not contortionists: Coupled adaptive learning for head and body orientation estimation in surveillance video
  • Cheng Chen, J. Odobez
  • Computer Science
    IEEE Conference on Computer Vision and Pattern…
  • 16 June 2012
TLDR
This paper addresses the estimation of body and head poses in surveillance videos as a joint model adaptation problem in a semi-supervised framework, and proposes a kernel-formulation of this principle that can be efficiently solved using a global optimization scheme.
Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition
TLDR
A semi-supervised hierarchical dynamic framework based on a Hidden Markov Model (HMM) is proposed for simultaneous gesture segmentation and recognition where skeleton joint information, depth and RGB images, are the multimodal input observations.
Using particles to track varying numbers of interacting people
TLDR
A Bayesian framework for the fully automatic tracking of a variable number of interacting targets using a fixed camera and a trans-dimensional Markov Chain Monte Carlo particle filter to recursively estimates the multi-object configuration and efficiently search the state-space is presented.
Gaze estimation from multimodal Kinect data
TLDR
A multimodal method that rely on depth sensing to obtain robust and accurate head pose tracking even under large head pose, and on the visual data to obtain the remaining eye-in-head gaze directional information from the eye image is proposed.
A Thousand Words in a Scene
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
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