InnovativeTeacher – Enhanced IT Skills in Education

In this paper we will describe the main criteria for the methodology handbook, the organisation of the repository and as well as the integration of the repository in Moodle eLearning platform as main communication basis for communication between teachers communities. We present also the results of a first teacher’s training with the instruments developed in the project

A New Fuzzy Additive Noise Reduction Method

In this paper we present a new alternative noise reduction method for color images that were corrupted with additive Gaussian noise. We illustrate that color images have to be processed in a different way than most of the state-of-the-art methods. The proposed method consists of two sub-filters. The main concern of the first subfilter is to distinguish between local variations due to noise and local variations due to image structures such as edges. This is realized by using the color component distances instead of component differences as done by most current filters. The second subfilter is used as a complementary filter which especially preserves differences between the color components. This is realized by calculating the local differences in the red, green and blue environment separately. These differences are then combined to calculate the local estimation of the central pixel. Experimental results show the feasibility of the proposed approach

Dissolve detection in abstract video contents

International audienceWe propose a straightforward intensity-based dissolve detection method which is able to cope with the particular constraints of the artistic animated movie domain. It uses the hypothesis that during a dissolve, the amount of fading-out and fading-in pixels should be high. Instead of just applying a global threshold, as most of the existing approaches do, we use a twin-threshold approach coped with shape analysis of the signal. This approach allows to reduce false detections caused by steep intensity fluctuations as well as to retrieve dissolves caught up in other visual effects. Experimental tests show that whether classic approaches tends to fail, the pro posed method provides a good detection even for very complex content setups (e.g. global movement, temporal discontinuity)

A Contour-Color-Action Approach to Automatic Classication of Several Common Video Genres

International audienceWe address the issue of automatic video genre retrieval. We propose three categories of content descriptors, extracted at temporal, color and structural level. At temporal level, video content is described with visual rhythm, action content and amount of gradual transitions. Colors are globally described with statistics of color distribution, elementary hues, color properties and relationship. Finally, structural information is extracted at image level and histograms are built to describe contour segments and their relations. The proposed parameters are used to classify 7 common video genres, namely: animated movies/cartoons, commercials, documentaries, movies, music clips, news and sports. Experimental tests using several classification techniques and more than 91 hours of video footage prove the potential of these parameters to the indexing task: despite the similarity in semantic content of several genres, we achieve detection ratios ranging between 80-100%

Automatic Tools for Diagnosis Support of Total Hip Replacement Follow-up

Total hip replacement is a common procedure in today orthopedics, with high rate of long-term success. Failure prevention is based on a regular follow-up aimed at checking the prosthesis fit and state by means of visual inspection of radiographic images. It is our purpose to provide automatic means for aiding medical personnel in this task. Therefore we have constructed tools for automatic identification of the component parts of the radiograph, followed by analysis of interactions between the bone and the prosthesis. The results form a set of parameters with obvious interest in medical diagnosis

A color-action perceptual approach to the classification of animated movies

International audienceWe address a particular case of video genre classification, namely the classification of animated movies. This task is achieved using two categories of content descriptors, temporal and color based, which are adapted to this particular content. Temporal descriptors, like rhy\-thm or action, are quantifying the perception of the action content at different levels. Color descriptors are determined using color perception which is quantified in terms of statistics of color distribution, elementary hues, color properties (e.g. amount of light colors, cold colors, etc.) and color relationship. The potential of the proposed descriptors to the classification task has been proved through experimental tests conducted on more than 159 hours of video footage. Despite the high diversity of the video material, the proposed descriptors achieve an average precision and recall ratios up to 90% and 92%, respectively, and a global correct detection ratio up to 92%