Speachreading using shape and intensity information
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It has been previously demonstrated that systems based on Hidden Markov Models (HMMs) are suitable for face recognition. The proposed approaches in the literature are either HMMs with one-dimensional (1D-HMMs) or two-dimensional (2D-HMMs) topology. Both ha ...
This paper presents a novel algorithm for robust object recognition. We propose to model the visual appearance of objects via probability density functions. The algorithm consists of a fully connected Markov random field with energy function derived from r ...
This paper introduces and motivates the use of Gaussian Mixture Models (GMMs) for on-line signature verification. The individual Gaussian components are shown to represent some local, signer-dependent features that characterise spatial and temporal aspects ...
This paper presents an approach for the segmentation of broadcast news into stories. The main novelty of this work is that the segmentation process does not take into account the content of the news, i.e. what is said, but rather the structure of the socia ...
This paper advocates an implicit-surface representation of generic 3--D surfaces to take advantage of occluding edges in a very robust way. This lets us exploit silhouette constraints in uncontrolled environments that may involve occlusions and changing or ...
We propose a fast texture-segmentation approach to the problem of 2-D and 3--D model-based contour tracking, which is suitable for real-time or interactive applications. Our approach relies on detecting texture boundaries in the direction normal to the con ...
In this paper, we address the problem of the recognition of isolated complex mono- and bi-manual hand gestures. In the proposed system, hand gestures are represented by the 3D trajectories of blobs. Blobs are obtained by tracking colored body parts in real ...
This thesis presents a PhD work on offline cursive handwriting recognition, the automatic transcription of cursive data when only its image is available. Two main approaches were used in the literature to solve the problem. The first one attempts to segmen ...
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often unrealistic assumptions on the conditional independence of observations given ...
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often unrealistic assumptions on the conditional independence of observations given ...
