- Seminar: Matrix completion, a vision-oriented pers… May 15th, 2016
I will be giving a seminar at INRIA, CMU and IRI on computer vision applications of matrix completion.
Matrix completion is a generic framework aiming to recover a matrix from a limited number of (possibly noisy) entries. In this content, low-rank regularizers are often imposed so as to find matrix estimators that are robust to noise ...
- The separation of moving sound sources @ WASPAA … May 14th, 2016
Dionyssos Kounades-Bastian, Laurent Girin, Xavier Alameda-Pineda, Sharon Gannot and Radu Horaud
The separation of moving sound sources is a challenging task mainly because it is extremely complex to devise algorithms that robustly discriminate those signal variations due to the intrinsic variation of the sound source from those signal variations due to the time-varying ...
- Non-Linear Matrix Completion @ CVPR’16 (Las … April 11th, 2016
Xavier Alameda-Pineda, Elisa Ricci, Yan Yan and Nicu Sebe
Advanced computer vision and machine learning techniques tried to automatically categorize the emotions elicited by abstract paintings with limited success. Since the annotation of the emotional content is highly resource-consuming, datasets of abstract paintings are either constrained in size or partially annotated. Consequently, it is natural to ...
- 2.5x @ IEEE CVPR 2016 (Las Vegas) March 10th, 2016
We’ve got two papers accepted at IEEE CVPR 2016:
Remote heart-rate estimation with self-adaptive matrix completion .
Recognize emotions from abstract paintings with non-linear matrix completion
Additionally I presented a paper on Recurrent Face Aging from the group.
- Weighted-data GMM @ IEEE TPAMI January 25th, 2016
Israel-Dejene Gebru, Xavier Alameda-Pineda, Florence Forbes and Radu Horaud
We recently got a paper accepted at TPAMI!
We had this crazy idea of mixture models that are trained with weighted-data. Imagine you want to train a GMM, and each data point comes with a weight denoting the relevance of the data point for the ...
- Low-rank inverse-gamma @ IEEE ICASSP 2016 (Shangai… January 20th, 2016
Dionyssis Kounades-Bastian, Laurent Girin, Xavier Alameda-Pineda, Sharon Gannot and Radu Horaud
Our low-rank parametrization of inverse-gamma distributions for speech modeling has been accepted at IEEE ICASSP 2016. The main idea is to parametrize the power-spectral density with an NMF-like model in which, even if the parameters are low-rank, the PSD is not. Indeed, ...
- The SALSA dataset December 12th, 2015
Xavier Alameda-Pineda, Jacopo Staiano, Ramanathan Subramanian, Ligia Batrinca, Elisa Ricci, Bruno Lepri, Oswald Lanz and Nicu Sebe
Keywords: Multimodal group behavior analysis, Free-standing conversational groups, multimodal social data sets, Tracking, Head and body pose estimation, Personality traits.
Synergetic sociAL Scene Analysis (SALSA) contains uninterrupted recordings of an indoor social event involving 18 subjects over 60 minutes. It serves as a rich ...
- Variational EM and non-convex optimization for mul… December 4th, 2015
Next december 22nd I will be giving a seminar at the Robot-Action-Perception team of LAAS/CNRS, whose abstract reads below.
In this talk I describe the mathematical foundations we used in the recent past to address four different multi–sensor scene analysis tasks, namely: audio-visual speaker detection and localization, separation of moving sound sources, geometric sound source localization ...
- Best Paper Award @ ACM Multimedia 2015 (Brisbane) October 31st, 2015
Xavier Alameda-Pineda, Yan Yan, Elisa Ricci, Oswald Lanz and Nicu Sebe
I happily announce that we received the Best Paper Award for
Analyzing free-standing conversational groups: a multimodal approach
at ACM International Conference in Multimedia 2015 (Brisbane, Australia) .
Abstract During natural social gatherings, humans tend to organize themselves in the so-called free-standing conversational groups. In ...
- Best Student Paper Award @ IEEE WASPAA 2015 (New P… October 25th, 2015
I am glad to announce that we got the Best Student Paper Award for
A Variational EM Algorithm for the Separation of Moving Sound Sources
at IEEE Workshop on Applications of Signal Processing to Audio and Acoustics 2015 (New Paltz, USA). See the topic’s page and .