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4 Papers

Hide and Seek - An Active Binocular Object Tracking System

Topics: Active and Robot Vision; Tracking and Visual Navigation; Vision for Robotics

Authors: Pramod Chandrashekhariah and Jochen Triesch

Affiliation: Johann Wolfgang Goethe University, Germany

Digital Object Identifier: 10.5220/0004690705840591

Proceedings of VISAPP 2014/VISIGRAPP, ISBN: 978-989-758-009-3

Collapse Button Quick Abstract
We introduce a novel active stereo vison-based object tracking system for a humanoid robot. The system tracks a moving object that is dynamically changing its appearance and scale. The system features an inbuilt learning process that simultaneously learns short term models for the object and potential distractors. These models evolve over time, rectifying the inaccuracies of the tracking in a cluttered scene and allowing the system to identify unusual events such as sudden displacement, hiding behind or being masked by an occluder, and sudden disappearance from the scene. The system deals with these through different response modes such as active search when the object is lost, intentional waiting for reappearance when the object is hidden, and reinitialization of the track when the object is suddenly displaced by the user. We demonstrate our system on the iCub robot in an indoor environment and evaluate its performance. Our experiments show a performance enhancement for long occlusions through the learning of distractor models.
Collapse Button Related Ontology Subjects/Areas/Topics (8)
Active and Robot Vision

Motion, Tracking and Stereo Vision

Software Engineering

Applications

Pattern Recognition

Tracking and Visual Navigation
Computer Vision, Visualization and Computer Graphics

Robotics

Let it Learn - A Curious Vision System for Autonomous Object Learning

Topics: Active and Robot Vision; Early and Biologically-Inspired Vision; Visual Attention and Image Saliency

Authors: Pramod Chandrashekhariah , Gabriele Spina and Jochen Triesch

Affiliation: Johann Wolfgang Goethe University, Germany

Digital Object Identifier: 10.5220/0004294101690176

Proceedings of VISAPP 2013/VISIGRAPP, ISBN: 978-989-8565-48-8

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We present a “curious” active vision system for a humanoid robot that autonomously explores its environment and learns object representations without any human assistance. Similar to an infant, who is intrinsically motivated to seek out new information, our system is endowed with an attention and learning mechanism designed to search for new information that has not been learned yet. Our method can deal with dynamic changes of object appearance which are incorporated into the object models. Our experiments demonstrate improved learning speed and accuracy through curiosity-driven learning.
Collapse Button Related Ontology Subjects/Areas/Topics (6)
Active and Robot Vision

Early and Biologically-Inspired Vision

Motion, Tracking and Stereo Vision

Computer Vision, Visualization and Computer Graphics

Image and Video Analysis

Visual Attention and Image Saliency

ICA CLEANING PROCEDURE FOR EEG SIGNALS ANALYSIS - Application to Alzheimer's Disease Detection

Authors: J. Solé-Casals 1 , F. Vialatte 2 , J. Pantel 3 , D. Prvulovic 3 , C. Haenschel 4 and A. Cichocki 5

Affiliations: 1 1Digital Technologies Group, University of Vic, Spain , 2 RIKEN Brain Science Institute, LABSP, Japan , 3 Johann Wolfgang Goethe University, Germany , 4 Bangor University, United Kingdom , 5 2RIKEN Brain Science Institute, LABSP, Japan

Digital Object Identifier: 10.5220/0002755904850490

Proceedings of Special Session on Neural Signals of Brain Disorde 2010/BIOSTEC, ISBN: 978-989-674-018-4

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To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude (≥100 μV). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure.

Enhancing Security of Terminal Payment with Mobile Electronic Signatures

Author: Evgenia Pisko

Affiliation: Johann Wolfgang Goethe-University, Germany

Digital Object Identifier: 10.5220/0002430900130022

Proceedings of WUC 2007/ICEIS, ISBN: 978-972-8865-94-8

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With the growing number of debit card transactions, security issues have arisen correspondingly. By applying the latest technical innovations, criminals are using more and more effective methods of card fraud. They are exploiting security weaknesses of existing debit card payment rules. For instance, if a criminal has acquired the complete card data, he will be then able to use it to withdraw money until the card is blocked. To authorize each payment and to guarantee the integrity of payment information, we have developed a service architecture for mobile signature secured payments at the POS, which we present in this paper. To support the proposed architecture we suggest service subscription and payment protocols.

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