Face Authentication Using Morphological Dynamic Link Architecture
A very attractive approach for face detection is based on multiresolution images (also known as mosaic images). Motivated by the simplicity of this approach, a rule-based face detection algorithm in frontal views is developed first. Second, a novel dynamic link architecture based on multiscale morphological dilation-erosion is proposed for face authentication. More specifically, a sparse grid is placed over the outcome of face detection stage for each person in a reference set. Subsequently, multiscale morphological operations are employed to yield a feature vector at each node of the grid and dynamic link matching is applied to verify the identity of each person from a test set. The first experimental results reported in this paper verify the superiority of the proposed method over the (standard) dynamic link matching that is based on Gabor wavelets.

title: Face authentication with Gabor information on deformable graphs
abstract: Elastic graph matching has been proposed as a practical implementation of dynamic link matching, which is a neural network with dynamically evolving links between a reference model and an input image. Each node of the graph contains features that characterize the neighborhood of its location in the image. The elastic graph matching usually consists of two consecutive steps, namely a matching with a rigid grid, followed by a deformation of the grid, which is actually the elastic part. The deformation step is introduced in order to allow for some deformation, rotation, and scaling of the object to be matched. This method is applied here to the authentication of human faces where candidates claim an identity that is to be checked. The matching error as originally suggested is not powerful enough to provide satisfying results in this case. We introduce an automatic weighting of the nodes according to their significance. We also explore the significance of the elastic deformation for an application of face-based person authentication. We compare performance results obtained with and without the second matching step. Results show that the deformation step slightly increases the performance, but has lower influence than the weighting of the nodes. The best results are obtained with the combination of both aspects. The results provided by the proposed method compare favorably with two methods that require a prior geometric face normalization, namely the synergetic and eigenface approaches.

title: Expert Conciliation for Multi Modal Person Authentication Systems by Bayesian Statistics
abstract: We present an algorithm functioning as a supervisor module in a multi expert decision making machine. It uses the Bayes theory in order to estimate the biases of individual expert opinions. These are then used to calibrate and conciliate expert opinions to one opinion. We present a framework for simulating decision strategies using expert opinions whose properties are easily modifiable. By using real data coming from a person authentication system using image and speech data we were able to confirm that the proposed supervisor improves the quality of individual expert decisions by reaching success rates of 99.5 %.

title: Automatic Identification of Diatoms Using Decision Forests
abstract: A feature based identification scheme for microscopic images of diatoms is presented in this paper. Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photo synthesis. The proposed automatic identification scheme follows a decision tree based classification approach. In this paper two different ensemble learning methods are evaluated and results are compared with those of single decision trees. As test sets two different diatom image databases are used. For each image in the databases general features like symmetry, geometric properties, moment invariants, and Fourier descriptors as well as diatom specific features like striae density and direction are computed.

title: The COSIMA prototype for multi-objective bargaining
abstract: Multi-objective bargaining is a challenging business model for B2C or B2B Internet applications. Our visual bargaining agent COSIMA builds on cooperative database technology like Preference SQL or Preference XPATH, which can efficiently implement \linebreak[4] multi-dimensional search engines with a Pareto-optimality semantics to find best alternative offers. COSIMA is a smart avatar with dynamically generated speech output. We have implemented several well-known bargaining strategies for a sample e-shop, where the customer can bargain on more attributes than just the price. The life-like appearance of COSIMA is supported by randomizing her bargaining tactics and by expressing visual emotions during bargaining. She can also learn and adapt dynamically to various bargaining preferences of the customers. The COSIMA prototype is carefully engineered by means of component-ware and IT-standards including SQL, XML and Java. This makes it scalable even to very large e-shop databases. Measurements show that this advanced user interface of COSIMA requires only a small overhead of a few seconds, including the bidding process. Thus real-time performance using state-of-the art software components and hardware is feasible. A preliminary user feedback has been very encouraging. COSIMA gave her debut to a large professional audience at the computer fair CeBIT 2002.

title: Optimizing the catalog search process for e-procurement platforms
abstract: Many e-procurement platforms support XML-based e-catalogs combined with standardized feature descriptions. Beyond the usual keyword search this opens the arena for attribute-based search engines, including parametric search and preference search. We analyze the impact of different search techniques for such e-catalogs on the overall search process costs. It turns out that preference search has a high potential to significantly reduce the process costs. A large-scale use case with the MAN2B e-procurement platform supports our claim. We identify improvements achievable by using preference search, in particular less navigation steps during the product search and better search results due to the BMO query model. Expensive cases, where frustrated users accept bad search results or phone up the company's purchasing department, should decrease significantly. This in turn will enable the purchasing department to focus more on strategic issues like supplier relationship management than on operative issues as it still happens widely today.

title: Identification of Diatoms by Grid Graph Matching
abstract: Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photo synthesis. In this paper a graph matching based identification approach for the retrieval of diatoms from an image database is presented. The retrieval is based on the matching of labeled grid graphs carrying texture information of the underlying diatom. A grid graph is a regular, rectangular arrangement of nodes overlaid on an image. Each node of the graph is labeled with texture features describing a rectangular sub-region of the object. Properties of gray level co-occurrence matrices as well as of Gabor wavelets are used as texture features. The method has been evaluated on a diatom database holding images of 188 different diatoms belonging to 38 classes. For the identification of these diatoms recognition rates of more than 90 percent were obtained.

title: How well does charge reparametrisation account for solvent screening in molecular mechanics calculations? The example of myosin
abstract: The rate constant of an enzyme-catalysed reaction is one of the major target properties to understand protein function. Atomic-detail computer simulations can in principle be used to estimate rate constants from the energy profile along the reaction coordinate. For such simulations, molecular mechanics is combined with a quantum description of the reaction process. In molecular mechanics calculations, the electrostatic field is represented by the Coulomb potential of partial atomic charges which have been parametrised for small building blocks in vacuum and transferred to the macromolecule. In aqueous solution, however, the electrostatic interactions are affected by the solvent polarization. While this can be described by numerically solving the Poisson-Boltzmann equation, it is computationally expensive. A simple approximation to this is to optimally reproduce the electrostatic potential in solution by reparametrising the partial atomic charges in such a way that a simple Coulomb potential can still be used. Such a procedure would allow to perform fast calculations of reaction processes in proteins while accounting for the solvent screening effect. Here, this method is tested on myosin, a motor protein that is both an enzyme and exists in very different conformations.