In this paper we address the problem of recognising interactions between two people in realistic scenarios for video retrieval purposes. We develop a per-person descriptor that uses attention (head orientation) and the local spatial and temporal context in a neighbourhood of each detected person. Using head orientation mitigates camera view ambiguities, while the local context, comprised of his...

Many structured light scanning systems based on temporal pattern codification produce dense and robust results on static scenes but behave very poorly when applied to dynamic scenes in which objects are allowed to move or to deform during the acquisition process. The main reason for this lies in the wrong combination of encoded correspondence information because the same point in the projector ...

Acknowledgements Everything started one day of June 2000, when I decided to go Erasmus at the Ecole Polytechnique in Paris, and I was suggested to attend there the databases lectures given by Prof. Abiteboul. When in January 2001, I decided to follow the extra-lectures of Prof. Abiteboul in order to present a databases project, he was so nice to sit beside me and teach me how to write my first ...

In user-facing applications, displaying calibrated confidence measures— probabilities that correspond to true frequency—can be as important as obtaining high accuracy. We are interested in calibration for structured prediction problems such as speech recognition, optical character recognition, and medical diagnosis. Structured prediction presents new challenges for calibration: the output space...

Significant advances in speech separation have been made by formulating it as a classification problem, where the desired output is the ideal binary mask (IBM). Previous work does not explicitly model the correlation between neighboring time-frequency units and standard binary classifiers are used. As one of the most important characteristics of speech signal is its temporal dynamics, the IBM c...

We formulate the problem of metric learning for k nearest neighbor classificationas a large margin structured prediction problem, with a latent variable representingthe choice of neighbors and the task loss directly corresponding to classificationerror. We describe an efficient algorithm for exact loss augmented inference, anda fast gradient descent algorithm for learning in thi...

This paper presents a completely automated facial action and facial expression recognition system using 2Dþ3D images recorded in real-time by a structured light sensor. It is based on local feature tracking and rule-based classification of geometric, appearance and surface curvature measurements. Several experiments conducted under relatively non-controlled conditions demonstrate the accuracy a...

Presented in this paper is an automated scanning procedure of a dental impression that utilizes an SLS (Structured Light System). The proposed procedure identifies missing areas from the initial scanning data from default orientations and attempts to locate additional scanning orientations to fill themissing areas. The core part of the proposed procedure is an algorithm that computes additional...

In structured prediction, it is standard procedure to discriminatively train a single model that is then used to make a single prediction for each input. This practice is simple but risky in many ways. For instance, models are often designed with tractability rather than faithfulness in mind. To hedge against such model misspecification, it may be useful to train multiple models that all are a ...