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Computer Vision
research related to computer vision
Neuroinformatics Group
Universität Bielefeld › Technische Fakultät › NI
Manipulation of paper is a rich domain of manual intelligence that we encounter in many daily tasks. The present project attempts to analyse and implement the "web" of visuo-motor coordination skills to endow an anthropomorphic robot hand with the ability to manipulate paper (and paper-like objects) in a variety of situations of increasing complexity. This will include aspects such as modeling interaction with compliant objects, action based representation as well as bimanual coordination to enable object transformations such as tearing and folding.
Unlike most existing approaches to the grasp selection task for anthropomorphic robot hands, this vision-based project aims for a solution, which does not depend on an a-priori known 3D shape of the object. Instead it uses a decomposition of the object view (obtained from mono or stereo cameras) into local, grasping-relevant shape primitives, whose optimal grasp type and approach direction are known or learned beforehand. Based on this decomposition a list of possible grasps can be generated and ordered according to the anticipated overall grasp quality.
In this project we are developing a system that is aimed to overcome a major limitation of current computer vision: The specialization of vision architectures to one special task. In this approach, artificial neural networks (ANN) are applied to learn the appearance of objects from samples images. By this means, the costly designing of geometric object models can be avoided. This work is realized in the framework NESSY (NEural viSion SYstem), a software package that allows an easy design and visualization of image processing systems. 
Common webcams yield a huge amount of images, but most of them are quite boring for lack of individual fascinating entities. In this project we analyse approaches of common image and video retrieval to develop a system for filtering interesting images shot by a webcam. 
Active Vision considers vision as a process of active data aquisition, i.e. actively pointing the cameras towards interesting regions within the scene, eventually changing zoom as well.