GeoNetwork: metadata and cataloging. French (GeoSource) and Swiss (geocat.ch) experiences

GeoNetwork opensource is a standards based, Free and Open Source catalog application to manage spatially referenced resources through the web. It is an OSGEO Project initiated by the Food and Agricultural Organization (FAO). The purpose of this presentation is to illustrate the implementation of such a catalog in national projects in France and in Switzerland. Firstly, we will present you the Geosource project undertaken by BRGM (http://www.brgm.fr/), gathering national and local authorities, national geographic survey, public organisations, associations in order to provide a metadata catalog for french users : definition of french iso profile, support for INSPIRE metadata requirements. Finally, we will present the SwissTopo geocat II project. The purpose of the project is to develop the next generation geospatial catalog for SwissTopo on the basis of GeoNetwork opensource. This both projects underline the closely collaboration between national authorities and the Geonetwork opensource community

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Use of decision trees in colour feature selection: application to object recognition in outdoor scenes

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields