In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to ...

We report research performed on gesture analysis and mapping to music. Various movements were recorded using 3D optical motion capture. Using this system, we produced animations from movements/dance, and generate in parallel the soundtrack from the dancer's movements. Prior to the actual sound mapping process, we performed various motion analyses. We present here two methods, both independent o...

The decomposition of a binary morphological structuring element is a well-known problem in pattern recognition that has often been addressed in the literature. Generally, only deterministic solutions have been considered, each relying on different assumptions. A different solution, with no such constraints, has been proposed by Anelli, Broggi and Destri: it is based on a stochastic evolutionary...

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The aim of this paper is to introduce multi­modal iden­ tity veri cation techniques to the InteractiveDialogue Sys­ tems society, and to identify possible applications. The multi­modal identity veri cation system presented here is based on two biometric modalities (speech and vision) and it uses 3 experts (using voice, frontal face and pro le images), based on these two modalities, in parallel....

In this note we will study upper bounds of random variables of the type sup A∈A |ν n (A) − ν(A)| , where A is a class of sets that needs to fulll certain assumptions. These bounds are important tools in the analysis of learning processes and probabilistic theories of pattern recognition. The presentation given here is based on [DGL96].

We propose a new algorithm for pattern recognition that outputs some measures of \reliability" for every prediction made, in contrast to the current algorithms that output \bare" predictions only. Our method uses a rule similar to that of nearest neighbours to infer predictions ; thus its predictive performance is close to that of nearest neighbours, while the measures of conndence it outputs p...

This paper introduces a novel approach for evaluating fabric sensory responses. First, the problems in existing techniques are analyzed, and by comparing with successful cases in assessing human feeling towards cold/warmth and human color sense, a more scientific scheme based on the computer pattern recognition technique is exhibited and the details of the measurements, data processing and calc...

Half away between edge detection and pattern recognition this study aim to characterize singularities in order to build closed edges and to classify object within an image.

In this study, a supervised pattern recognition technique is used to examine Long Term Geoelectric Potential difference (LTGP) data recorded during the 1993-1997 period in Western Greece. It presents initial results from an attempt towards automated discovery of similarities between LTGP data recorded during periods of similar seismic activity. In particular, we investigate whether patterns exi...