Jérôme Meessen

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— In this paper, we propose a new object-based video coding/transmission system using the emerging Motion JPEG 2000 standard [1] for the efficient storage and delivery of video surveillance over low bandwidth channels. Some recent papers deal with JPEG 2000 coding/transmission based on the Region Of Interest (ROI) feature and the multi-layer capability(More)
— In video surveillance applications, pre-stored images are likely to be accessed remotely and interactively upon user request. In such a context, the JPEG 2000 still image compression format is attractive because it supports flexible and progressive access to each individual image of the pre-stored content, in terms of spatial location, quality level, as(More)
This paper presents a classifier-based approach to recognize dynamic events in video surveillance sequences. The goal of this work is to propose a flexible event recognition system that can be used without relying on a long-term explicit tracking procedure. It is composed of three stages. The first one aims at defining and building a set of relevant(More)
A novel method for content-based retrieval of surveillance video data is presented. The study starts from the realistic assumption that the automatic feature extraction is kept simple, i.e. only segmenta-tion and low-cost filtering operations have been applied. The solution is based on a new and generic dissimilarity measure for discriminating video(More)
The image compression standard JPEG 2000 offers a high compression ef¿ciency as well as a great Àexibility in the way it accesses the content in terms of spatial location, quality level, and resolution. This paper explores how transmission systems conveying video surveillance sequences can bene¿t from this Àexibility. Rather than transmitting each frame(More)
This paper tackles the challenge of interactively retrieving visual scenes within surveillance sequences acquired with fixed camera. Contrarily to today's solutions , we assume that no a-priori knowledge is available so that the system must progressively learn the target scenes thanks to interactive labelling of a few frames by the user. The proposed method(More)
Globalisation of people's interaction in the industrial world and ecological cost of transport make video­conference an interesting solution for collaborative work. However, the lack of immersive perception makes video­conference not appealing. TIFANIS 1 tele­immersion system was conceived to let users interact as if they were physically together. In this(More)
Supervised learning of an ensemble of randomized trees is considered to recognize classes of events in topologically structured data (e.g. images or time series). We are primarily interested in classification problems that are characterized by severe scarcity of the training samples. The main idea of our paper consists in favoring the selection of(More)
By embedding multiple proximal SVM classifiers into a binary tree architecture, it is possible to turn an arbitrary multi-classes problem into a hierarchy of binary classifications. The critical issue then consists in determining in each node of the tree how to aggregate the multiple classes into a pair of say overlay classes to discriminate. As a(More)
Nowadays, video-conference tends to be more and more advantageous because of the economical and ecological cost of transport. Several platforms exist. The goal of the TIFANIS immersive platform is to let users interact as if they were physically together. Unlike previous teleimmersion systems, TIFANIS uses generic hardware to achieve an economically(More)