This paper presents an image classi cation algorithm using a multiresolution two dimensional hidden Markov model (HMM). The multiresolution two dimensional hidden Markov model is an extension from the two dimensional hidden Markov model for image classi cation. A classi er estimates model parameters using the EM algorithm. Classi cation is then performed according to the maximum a posteriori pr...

AbstractIn this paper, we evaluate the performance of a spatial multiresolution analysis (SMA) method, that behaves like variable bandwidth kernel density estimation (KDE) for hazardous r...

In this paper we explore the use of features derived from multiresolution analysis of speech and the Teager Energy Operator for classi cation of drivers' speech under stressed conditions. We apply this set of features to a database of short speech utterances to create userdependent discriminants of four stress categories. In addition we address the problem of choosing a suitable temporal scale ...

The notion of a multiresolution support is introduced. This is a sequence of boolean images, related to signi cant pixels at each of a number of resolution levels. The multiresolution support is then used for noise suppression, in the context of image ltering, or iterative image restoration. Algorithmic details, and a range of practical examples, illustrate this approach.

It has been previously shown that L-systems can be used to generate subdivision and reverse subdivision curves [Prusinkiewicz et al. 2003]. In this paper we show that L-systems can also be used to generate multiresolution curves. The L-system description captures the locality of the concept of multiresolution curves.

We summarize the properties of the auto-correlation functions of compactly supported wavelets, their connection to iterative interpolation schemes, and the use of these functions for multiresolution analysis of signals. We briefly describe properties of representations using dilations and translations of these autocorrelation functions (the auto-correlation shell) which permit multiresolution a...

The problem of efficiently accessing and maintaining adjacency information for triangulations over general surface domains is addressed. Rapid access to adjacent vertices, edges, and triangles is an important aspect of multiresolution techniques, from subdivision surfaces to mesh simplification. Novel data structures and algorithms for the construction, manipulation, and traversal of triangulat...

This paper concerns with iterative schemes for the perfect reconstruction of functions belonging to multiresolution spaces on bounded manifolds from nonuniform sampling. The schemes have optimal complexity in the sense that the computational cost to achieve a certain fixed accuracy is proportional to the computed quantity. Since the iterations converge uniformly, one can produce corresponding i...

Very large graphics models are common in a number of applications, and many di erent simpli cation methods have been recently developed. Some of them support the construction of multiresolution representations of the input meshes. On the basis of these innovative techniques, we foresee a modeling framework based on three separate stages (shape modeling, multiresolution encoding and resolution m...

Multiresolution shape representation is a very effective way to decompose surface geometry into several levels of detail. Geometric modeling with such representations enables flexible modifications of the global shape while preserving the detail information. Many schemes for modeling with multiresolution decompositions based on splines, polygonal meshes and subdivision surfaces have been propos...