A new hand gesture recognition method based on Input– Output Hidden Markov Models is presented. This method deals with the dynamic aspects of gestures. Gestures are extracted from a sequence of video images by tracking the skin–color blobs corresponding to the hand into a body– face space centered on the face of the user. Our goal is to recognize two… (More)
This article present a method for real time hand and head tracking, in three dimensions, using two cameras. This tracking is intended as a first step for a gesture recognition system, using the trajectories of the hands, or as input to a real time clone animation system. The method used is based on simple preprocessings followed by the use of a statistical… (More)
Recently, there has been a lot of papers published in the eld of time series prediction using connectionist models. Nevertheless we think that one of the major problem which is rarely treated in the literature is related to the choice of input parameters (embedding dimension and delay). In this paper, we propose two modular approaches to this problem and… (More)
Both visual and acoustical informations provide effec– tive means of telecommunication between persons. In this context, the face is the most important part of the person both visually and acoustically. We describe how the co– operation of image and audio processing allows to track a person's face and to collect the audio information it pro– duces. We… (More)
In this paper, we propose some improvements for the problem of time series prediction with neural networks where a medium-term prediction horizon is needed. In particular, the ionospheric prediction service of the french Centre National d' Etudes des T el ecommunica-tions needs a six-month ahead prediction of a sunspots related time series which has a… (More)
Accurate prediction of ionospheric parameters is crucial for telecom-munication companies. These parameters strongly rely on solar activity. In this paper, we analyze the use of neural networks for sunspots time series prediction. Three types of models are tested and experimental results are reported for a particular sunspots time series: the IR5 index.
We present a neural network approach to human face detection. Using a modular system, a conditional mixture of networks, we are able to detect front view faces as well as turned faces (up to 50 degrees) with excellent performances. This modular network is integrated into LISTEN, our face tracking system. It enables this system to detect and track in… (More)
Using real traac data, we show that neural network-based prediction techniques can be used to predict the queuing behaviour of highly bursty traacs typical of LAN interconnection in a way accurate enough so as to allow dynamical renegotiation of a DBR traac contract at the edge of an ATM network. The performances of predictor-based in service renegotiation… (More)