Eurécom at TRECVid 2006: Extraction of High-level Features and BBC Rushes Exploitation

For the four year we have participated to the high-level feature extraction task and we pursued our e ort on the fusion of classifier outputs. Unfortunatly a single run was submitted for evaluation this year, due to lack of computationnal ressources during the limited time available for training and tuning the entire system. This year’s run is based on a SVM classification scheme. Localised color and texture features were extracted from shot key-frames. Then, SVM classifiers were build per concept on the training data set. The fusion of classifier outputs is finally provided by a multilayer neural network. In BBC rushes exploitation, we explore the description of rushes through a visual dictionary. A set of non-redundant images are segmented into blocks. These blocks are clustered in a small number of classes to create a visual dictionary. Then, we can describe each image by the number of blocks of each class. After, we evaluate the power of this visual dictionary for retrieving images from rushes: if we use one or more blocks from an image as a query, are we able to retrieve the original image, and in which position in the result list. And finally, we organize and present video using this visual dictionary.