Connected image processing with multivariate attributes: an unsupervised Markovian classification approach

International audienceThis article presents a new approach for constructing connected operators for image processing and analysis. It relies on a hierarchical Markovian unsupervised algorithm in order to classify the nodes of the traditional Max-Tree. This approach enables to naturally handle multivariate attributes in a robust non-local way. The technique is demonstrated on several image analysis tasks: filtering, segmentation, and source detection, on astronomical and biomedical images. The obtained results show that the method is competitive despite its general formulation. This article provides also a new insight in the field of hierarchical Markovian image processing showing that morphological trees can advantageously replace traditional quadtrees

Segmentation semi-automatique de corpus vidéo en Langue des Signes

Session "Articles"National audienceDe nombreuses études sont en cours afin de développer des méthodes de traitement automatique de langues des signes. Plusieurs approches nécessitent de grandes quantités de données annotées pour l'apprentissage des systèmes de reconnaissance. Nos travaux s'occupent de l'annotation semi-automatique afin de permettre de collecter les données. Nous proposons une méthode de suivi de composantes corporelles, de segmentation de la main pendant occultation et de segmentation des gestes à l'aide des caractéristiques de mouvement et de forme de la mai

A hybrid formalism to parse sign languages

International audienceSign Language (SL) linguistic is dependent on the expensive task of annotating. Some automation is already available for low-level information (eg. body part tracking) and the lexical level has shown significant progresses. The syntactic level lacks annotated corpora as well as complete and consistent models. This article presents a solution for the automatic annotation of SL syntactic elements. It exposes a formalism able to represent both constituency-based and dependency-based models. The first enable the representation the structures one may want to annotate, the second aims at fulfilling the holes of the first. A parser is presented and used to conduct two experiments on the solution. One experiment is on a real corpus, the other is on a synthetic corpus

Sign language lexical recognition with Propositional Dynamic Logic

International audienceThis paper explores the use of Propositional Dynamic Logic (PDL) as a suitable formal framework for describing Sign Language (SL), the language of deaf people, in the context of natural language processing. SLs are visual, complete, standalone languages which are just as expressive as oral languages. Signs in SL usually correspond to sequences of highly specific body postures interleaved with movements, which make reference to real world objects, characters or situations. Here we propose a formal representation of SL signs, that will help us with the analysis of automatically-collected hand tracking data from French Sign Language (FSL) video corpora. We further show how such a representation could help us with the design of computer aided SL verification tools, which in turn would bring us closer to the development of an automatic recognition system for these languages

Implementation of an Automatic Sign Language Lexical Annotation Framework based on Propositional Dynamic Logic

International audienceIn this paper, we present the implementation of an automatic Sign Language (SL) sign annotation framework based on a formal logic, the Propositional Dynamic Logic (PDL). Our system relies heavily on the use of a specific variant of PDL, the Propositional Dynamic Logic for Sign Language (PDLSL), which lets us describe SL signs as formulae and corpora videos as labeled transition systems (LTSs). Here, we intend to show how a generic annotation system can be constructed upon these underlying theoretical principles, regardless of the tracking technologies available or the input format of corpora. With this in mind, we generated a development framework that adapts the system to specific use cases. Furthermore, we present some results obtained by our application when adapted to one distinct case, 2D corpora analysis with pre-processed tracking information. We also present some insights on how such a technology can be used to analyze 3D real-time data, captured with a depth device

Mise en sécurité des carrières souterraines

International audiencePillar failure in underground quarries can generate surface subsidence with public safety and environmental implications can be severe. In this context, various preventing and protecting methods such as the backfilling of cavities, should be used to control and to settle the hazards linked to underground quarries. The lines to select the most appropriate solution are the cost of the operation, the technical data (accessibility and stability of the site), the planned land use, the aims of the prevention. This article synthesizes the economical and technical advantages or disadvantages for each preventing or protecting method.Les manifestations en surface des désordres se produisant dans les carrières souterraines peuvent engendrer de graves conséquences en termes de sécurité publique, de dégâts sur le bâti et d'impacts sur l'environnement. Dans ce contexte, différentes techniques de prévention et de protection, telles que le remblayage des vides, sont alors à mettre en oeuvre pour maîtriser et traiter les risques induits par ces travaux. Le choix entre ces différentes méthodes dépend des conditions générales d'accessibilité et de stabilité du site, de la destination de l'ouvrage souterrain, du niveau de protection souhaité et du coût de l'opération. Cet article présente une synthèse des techniques de traitement des cavités souterraines, en indiquant leurs avantages et leurs inconvénients, autant d'un point de vue technique qu 'économique

Toward a new axiomatic for hyper-connections

International audienceWe propose an evolution of the hyper-connection axiomatic in order to improve the consistency of hyper-connected filters and to simplify their design. Our idea relies on the principle that the decomposition of an image into h-components must be necessary and sufficient. We propose a set of three equivalent axioms to achieve this goal. We show that an existing h-connection already fulfills these axioms and we propose a new h-connection based on flat functions that also fulfills these axioms. Finally we show that these new axioms bring several new interesting properties that simplify the use of h-connections and guarantee the consistency of h-connected filters as they ensure that: 1) every deletion of image components will effectively modify the filtered image 2) a deleted component can not reappear in the filtered image

Hidden fuzzy Markov chain model with K discrete classes

International audienceThis paper deals with a new unsupervised fuzzy Bayesian segmentation method based on the hidden Markov chain model, in order to separate continuous from discrete components in the hidden data. We present a new F-HMC (fuzzy hidden Markov chain) related to three hard classes, based on a general extension of the previously algorithms proposed. For a given observation, the hidden variable owns a density according to a measure containing Dirac and Lebesgue components. We have performed our approach in the multispectral context. The hyper-parameters are estimated using a Stochastic Expectation Maximization (SEM) algorithm. We present synthetic simulations and also segmentation results related to real multi-band data