Jean-luc Bloechle

Penalty kicks are increasingly decisive in major international football competitions. Yet, over 30% of shootout kicks are missed. The outcome of the kick often relies on the ability of the penalty taker to exploit anticipatory movements of the goalkeeper to redirect the kick toward the open side of the goal. Unfortunately, this ability is difficult to train using classical methods. We used an augmented reality simulator displaying an holographic goalkeeper to test and train penalty kick performance with 13 young elite players. Machine learning algorithms were used to optimize the learning rate by maintaining an optimal level of training difficulty. Ten training sessions of 20 kicks reduced the redirection threshold by 120 ms, which constituted a 28% reduction with respect to the baseline threshold. Importantly, redirection threshold reduction was observed for all trained players, and all things being equal, it corresponded to an estimated 35% improvement of the success rate.

In order to study the impact of increased mental workload on motion detection, twenty-four observers performed a motion discrimination task in which they had to detect odd moving patches. Two types of moving patches were used, namely luminance-based and contrast-based patches. For both types of patches, the motion discrimination task was performed with and without an additional N-Back task aimed at increasing the mental workload. The dual task decreased discrimination performance for both types of patches, but the difference was significantly larger for contrast-based patches, i.e., for second-order motion stimuli, both as an absolute and relative increment. This suggests that motion discrimination requires larger cognitive resources for contrast-based than for luminance-based stimuli, thereby hinting at the higher complexity of the cognitive mechanisms underlying second-order motion detection.

... A shape map is created from the bounding box of CCs in a page. Theses shapes are classified into noise, graphics, and text, according to their sizes. ... A scenario is a kind of macro defining the position of a block, its relation to the neighborhood blocks, its shape, and its content. ...

Abstract. Accessing the structured content of PDF document is a difficult task, requiring pre-processing and reverse engineering techniques. In this paper, we first present different methods to accomplish this task, which are based either on document image analysis, or on electronic content extraction. Then, XCDF, a canonical format with well-defined properties is proposed as a suitable solution for representing structured electronic documents and as an entry point for further researches and works. The system and methods used for reverse engineering PDF document into this canonical format are also presented. We finally present current applications of this work into various domains, spacing from data mining to multimedia navigation, and consistently benefiting from our canonical format in order to access PDF document content and structures. 1.

Physical and logical structure recovering from electronic documents is still an open issue. In this paper, we propose a flexible and efficient approach for recovering document structures from PDF files. After a brief introduction of the PDF format and its major features, we report about our evaluation of different existing tools and works for PDF content extraction and analysis. To overcome the weaknesses of these systems, we propose a new analysis strategy, based on an intermediate representation, called XCDF, which enables representing physical structures in a canonical way. This paper then describes the PDF reverse engineering workflow and focuses on the document logical restructuring. Finally, the paper concludes with potential future improvements. 1.

This article presents Xed, a reverse engineering tool for PDF documents, which extracts the original document layout structure. Xed mixes electronic extraction methods with state-of-the-art document analysis techniques and outputs the layout structure in a hierarchical canonical form, i.e. which is universal and independent of the document type. This article first reviews the major traps and tricks of the PDF format. It then introduces the architecture of Xed along with its main modules, and, in particular, the document physical structure extraction algorithm. Later on, a canonical format is proposed and discussed with an example. Finally the results of a practical evaluation are presented, followed by an outline of future works on the logical structure extraction.

Revealing and being able to manipulate the structured content of PDF documents is a difficult task, requiring pre-processing and reverse engineering techniques. In this paper, we present OCD, an optimized, easy-to-process and canonical format for representing structured electronic documents. The system and methods used for reverse engineering PDF documents into the OCD format are presented as well as the techniques to optimize it. We finally expose concrete evaluations of our OCD format compactness and restructuring performances. 1.

We are proposing in this paper an automated system to verify that images are correctly associated to labels. The novelty of the system is in the use of Gaussian Mixture Models (GMMs) as statistical modeling scheme as well as in several improvements introduced specifically for the verification task. Our approach is evaluated using the Caltech 101 database. Starting from an initial baseline system providing an equal error rate of 27.4%, we show that the rate of errors can be reduced down to 13% by introducing several optimizations of the system. The advantage of the approach lies in the fact that basically any object can be generically and blindly modeled with limited supervision. A potential target application could be a post-filtering of images returned by search engines to prune out or reorder less relevant images.

Acceder au contenu structure d'un document PDF est une tâche complexe dependante de methodes de pre-traitement et de retro-ingenierie. Cet article decrit le format canonique XCDF utilise pour la representation des resultats d'extraction et d'analyse des structures physiques de documents PDF. Ce format est positionne par rapport aux autres recherches, puis detaille d'un point de vue theorique. XED, l'outil realisant la transformation de fichiers PDF vers le format XCDF est ensuite brievement presente. L'interet de XCDF est finalement illustre a l'aide de plusieurs exemples d'applications concretes mettant en evidence son role central lors d'analyses de plus haut niveau.

We are proposing in this paper an automated system to verify that images are correctly associated to labels. The novelty of the system is in the use of Gaussian Mixture Models (GMMs) as statistical modeling scheme as well as in several improvements introduced specifically for the verification task. Our approach is evaluated using the Caltech 101 database. Starting from an

... A shape map is created from the bounding box of CCs in a page. Theses shapes are classified into noise, graphics, and text, according to their sizes. ... A scenario is a kind of macro defining the position of a block, its relation to the neighborhood blocks, its shape, and its content. ...

Le format PDF est devenu depuis plusieurs années le format de prédilection pour l'échange de documents imprimables. Cependant, ce format complexe est utilisé généralement uniquement pour l'affichage des documents. Les capacités de description des structures logiques intégrées au format sont ignorées, avec pour conséquence l'entassement de documents PDF sans la moindre métadonnée pouvant aider à cibler leur contenu.