Showing papers by "Constantine Kotropoulos published in 2003"

ICA and Gabor representation for facial expression recognition

Abstract: Two hybrid systems for classifying seven categories of human facial expression are proposed The first system combines independent component analysis (ICA) and support vector machines (SVMs) The original face image database is decomposed into linear combinations of several basis images, where the corresponding coefficients of these combinations are fed up into SVMs instead of an original feature vector comprised of grayscale image pixel values The classification accuracy of this system is compared against that of baseline techniques that combine ICA with either two-class cosine similarity classifiers or two-class maximum correlation classifiers, when we classify facial expressions into these seven classes We found that, ICA decomposition combined with SVMs outperforms the aforementioned baseline classifiers The second system proposed operates in two steps: first, a set of Gabor wavelets (GWs) is applied to the original face image database and, second, the new features obtained are classified by using either SVMs or cosine similarity classifiers or maximum correlation classifier The best facial expression recognition rate is achieved when Gabor wavelets are combined with SVMs

Video shot segmentation using singular value decomposition

Abstract: A new method for detecting shot boundaries in video sequences using singular value decomposition (SVD) is proposed. The method relies on performing singular value decomposition on the matrix A created from 3D histograms of single frames. We have used SVD for its capabilities to derive a low dimensional refined feature space from a high dimensional raw feature space, where pattern similarity can easily be detected. The method can detect cuts and gradual transitions, such as dissolves and fades, which cannot be detected easily by entropy measures.

CAML – A Universal Configuration Language for Dialogue Systems

Abstract: In this paper, a novel architecture of a universal dialogue system and its configuration language, so-called Conversational Agent Markup Language (CAML), is proposed. The dialogue system embodies a CLIPS engine in order to enable CAML to formulate procedural and heuristic knowledge. CAML supports frames, functions, and categories that enable it: (a) to process wildcards, to control the inner state through variables, and to formulate procedural knowledge in contrast to Phoenix/CAT Dialog Manager; (b) to support nested macros, to control the inner state through variables, to assign priorities and weights to states, and to interface with external databases in contrast to Dialog Management Tool Language (DMTL); (c) to implement context-free grammars, to extract semantic content from user input through frames, to allow numeric variables, and to interface with external databases as opposed to Artificial Intelligence Markup Language (AIML). The proposed system is extensible in the sense that it can be embedded in any conversational system that receives and emits XML content. Such a dialogue system can be incorporated in multimodal interfaces, such as talking head applications, conversational web interfaces, conversational database interfaces, and conversational programming interfaces.

Partly-Specified Priority Patterns in Natural Language Parsing within Dialogue Systems

Abstract: In this paper, two essential problems that belong to language parsing and have arisen from dialogue management are discussed and solved by implementing a variant of the well-known context-free parsing algorithm [1]. The first problem is the use of partly specified patterns, i.e., the use of wildcards in the right-hand-sides of the rewriting rules of a context-free grammar. The second one is the use of priority patterns, i.e., the assignment of priority values to rewriting rules. These problems are not handled in the majority of the state-of-the-art dialogue systems. The proposed algorithm has been implemented in a dialogue system core application called CAML Core [7], that is used to implement dialogue systems in several domains like conversational and multimodal interfaces for help desk applications, and chat bots.

CAML: A universal configuration language for dialogue systems

Abstract: In this paper, a novel architecture of a universal dialogue system and its configuration language, so-called Conversational Agent Markup Language (CAML), is proposed. The dialogue system embodies a CLIPS engine in order to enable CAML to formulate procedural and heuristic knowledge. CAML supports frames, functions, and categories that enable it: (a) to process wildcards, to control the inner state through variables, and to formulate procedural knowledge in contrast to Phoenix/CAT Dialog Manager; (b) to support nested macros, to control the inner state through variables, to assign priorities and weights to states, and to interface with external databases in contrast to Dialog Management Tool Language (DMTL); (c) to implement context-free grammars, to extract semantic content from user input through frames, to allow numeric variables, and to interface with external databases as opposed to Artificial Intelligence Markup Language (AIML). The proposed system is extensible in the sense that it can be embedded in any conversational system that receives and emits XML content. Such a dialogue system can be incorporated in multimodal interfaces, such as talking head applications, conversational web interfaces, conversational database interfaces, and conversational programming interfaces.