Learning part-based spatial models for laser-vision-based room categorization

Room categorization, that is, recognizing the functionality of a never before seen room, is a crucial capability for a household mobile robot. We present a new approach for room categorization that is based on two-dimensional laser range data. The method is based on a novel spatial model consisting of mid-level parts that are built on top of a low-level part-based representation. The approach is then fused with a vision-based method for room categorization, which is also based on a spatial model consisting of mid-level visual parts. In addition, we propose a new discriminative dictionary learning technique that is applied for part-dictionary selection in both laser-based and vision-based modalities. Finally, we present a comparative analysis between laser-based, vision-based, and laser-vision-fusion-based approaches in a uniform part-based framework, which is evaluated on a large dataset with several categories of rooms from domestic environments. </jats:p

Robot George: interactive continuous learning of visual concepts

The video presents the robot George learning visual concepts in dialogue with a tuto

Sharing Computer Vision Algorithms Over the World Wide Web

In this article we explore different possibilities of using the Internet for making computer vision algorithms publicly available. We describe how to build an interactive client/server application which uses World Wide Web for communication. The client program is a Java applet, while the server program works on the server as a CGI program. A stand-alone program for image segmentation was transformed into a Javaclient /CGI-server application, which can be used as a service on the World Wide Web. 1 Introduction Researchers in the field of computer vision work on different computers using various operating systems. Therefore it is very difficult to make the software available to the others in a convenient way because of different platforms being used. Fortunately, the Internet provides the means for communication across different platforms. Researchers can exchange messages, discuss problems in discussion groups, This work was supported by the Ministry of Science and Technology of Rep..

A System for Continuous Learning of Visual Concepts

We present an artificial cognitive system for learning visual concepts. It comprises of vision, communication and manipulation subsystems, which provide visual input, enable verbal and non-verbal communication with a tutor and allow interaction with a given scene. The main goal is to learn associations between automatically extracted visual features and words that describe the scene in an open-ended, continuous manner. In particular, we address the problem of cross-modal learning of visual properties and spatial relations. We introduce and analyse several learning modes requiring different levels of tutor supervision

A System for Continuous Learning of Visual Concepts

We present an artificial cognitive system for learning visual concepts. It comprises of vision, communication and manipulation subsystems, which provide visual input, enable verbal and non-verbal communication with a tutor and allow interaction with a given scene. The main goal is to learn associations between automatically extracted visual features and words that describe the scene in an open-ended, continuous manner. In particular, we address the problem of cross-modal learning of visual properties and spatial relations. We introduce and analyse several learning modes requiring different levels of tutor supervision

Self-understanding and self-extension: a systems and representational approach

There are many different approaches to building a system that can engage in autonomous mental development. In this paper we present an approach based on what we term em self-understanding, by which we mean the use of explicit representation of and reasoning about what a system does and doesn't know, and how that understanding changes under action. We present a coherent architecture and a set of representations used in two robot systems that exhibit a limited degree of autonomous mental development, what we term em self-extension. The contributions include: representations of gaps and uncertainty for specific kinds of knowledge, and a motivational and planning system for setting and achieving learning goal