Structured manifolds for motion production and segmentation : a structured Kernel Regression approach

Steffen JF. Structured manifolds for motion production and segmentation : a structured Kernel Regression approach. Bielefeld (Germany): Bielefeld University; 2010

Computational Neural Models of Spatial Integration in Perceptual Grouping

Recent developments in the neural computational modeling of perceptual grouping are described with reference to a newly proposed taxonomy to formalize mechanisms of spatial integration. This notational framework and nomenclature is introduced in or-der to clarify key properties common to all or most models, while permitting unique attributes of each approach to be independently examined. The strength of spatial integration in the models that are considered is always some function of the distances and relative alignments in perceptual space of the centers of units representing orien-tational features or energy in a visual scene. We discuss the signicance of variations of the constituents of an activation function for spatial integration, and also consider the larger modeling framework in which this function is applied in each approach. We also discuss the relationship of feedforward and feedback mechanisms and the issues of self-organization as core principles underlying the establishment of spatial integra-tion mechanisms. The relationship of the grouping models to models of other visual competencies is considered with respect to prospects for future research. 354 From Fragments to Object

Automated interpretation of digital images of hydrographic charts.

Details of research into the automated generation of a digital database of hydrographic charts is presented. Low level processing of digital images of hydrographic charts provides image line feature segments which serve as input to a semi-automated feature extraction system, (SAFE). This system is able to perform a great deal of the building of chart features from the image segments simply on the basis of proximity of the segments. The system solicits user interaction when ambiguities arise. IThe creation of an intelligent knowledge based system (IKBS) implemented in the form of a backward chained production rule based system, which cooperates with the SAFE system, is described. The 1KBS attempts to resolve ambiguities using domain knowledge coded in the form of production rules. The two systems communicate by the passing of goals from SAFE to the IKBS and the return of a certainty factor by the IKBS for each goal submitted. The SAFE system can make additional feature building decisions on the basis of collected sets of certainty factors, thus reducing the need for user interaction. This thesis establishes that the cooperating IKBS approach to image interpretation offers an effective route to automated image understanding

Segmentation of color images : applications to cellular microscopy

A morphological method for the color segmentation of cytological images is presented. This method is mainly based on watershed whose potential function blend local and global informations. The method uses a priori informations for the frame of the method. The paper is based on three parts. In a first part, the frame of a morphological segmentation method is recalled. Secondly, our morphological method of color segmentation is presented and its corresponding methodology of utilization is developped. All importants points of our morphological method are exposed : choice of the color space, choice of the color gradient, etc. Finally, the usefulness of the segmentation method is illustrated on images from serous cytology.Nous proposons une méthode morphologique de segmentation d'images couleur de cytologie. Cette méthode est basée sur la ligne de partage des eaux utilisant une fonction de potentiel couleur combinant informations locale et globale. Cette méthode de segmentation utilise des informations a priori pour élaborer l'utilisation de la méthode. L'article s'articule autour de trois parties. Dans une première partie, nous rappellerons tout d'abord la structure d'une segmentation morphologique couleur. Dans une deuxième partie, nous exposerons notre méthode morphologique de segmentation couleur ainsi que sa méthodologie d'utilisation précisant tous les points importants et leur mise au point (choix de l'espace couleur, choix du gradient, etc.). Dans une dernière partie nous verrons une illustration de la méthode de segmentation sur des images de la cytologie des séreuses

Advances in Character Recognition

This book presents advances in character recognition, and it consists of 12 chapters that cover wide range of topics on different aspects of character recognition. Hopefully, this book will serve as a reference source for academic research, for professionals working in the character recognition field and for all interested in the subject

Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics

This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ∼ 7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p

FUNCTION-DRIVEN APPROACHES TO THE DESIGN OF OPTOGENETIC TOOLS

Proteins play a wide variety of roles in biology despite being produced from a small set of common subunits; this commonality can be exploited to understand the dynamics by which proteins fold into structures and perform their manifold functions and, subsequently, design new proteins for use both in research and as nanoscale machines in industry. While this design process has classically involved residue-level redesign of existing protein backbones and, more recently, the de novo design of backbones according to geometrical parameters, the increasing complexity of optogenetic photosystems, biosensors, and other mechanisms for making use of proteins with specific functions has established a need for a design protocol that can reconcile their various structural exigencies with the function-specific elements of as wide an array of proteins as possible in order to make best use of them. Requirement-driven design eschews specific structural templates in favor of general requirements dependent on the intended function of the design, and so can exploit the vastness of protein structural space in finding solutions to increasingly complex design problems. Here, we present three new advances in the requirement-driven design of proteins as diagnostic tools, including a more general photosystem for the direct optogenetic control of protein-protein interactions, a series of algorithmic improvements to the leading implementation of requirement-driven design in the Rosetta macromolecular design software suite, and a new version of that algorithm capable of performing requirement-driven backbone design and residue-level backbone optimization simultaneously. These technologies collectively represent a significant improvement in our ability to control the activity of proteins with a wide variety of control schemes and produce functional proteins for arbitrary requirement sets more generally.Doctor of Philosoph