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Book ChapterDOI

A fast visual search and recognition mechanism for real-time robotics applications

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TLDR
A fast visual landmark search and recognition mechanism for real-time robotics applications that models two stages of visual perception named preattentive and attentive stages and shows validity and applicability to autonomous robot applications.
Abstract
Robot navigation relies on a robust and real-time visual perception system to understand the surrounding environment This paper describes a fast visual landmark search and recognition mechanism for real-time robotics applications The mechanism models two stages of visual perception named preattentive and attentive stages The pre-attentive stage provides a global guided search by identifying regions of interest, which is followed by the attentive stage for landmark recognition The results show the mechanism validity and applicability to autonomous robot applications.

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Citations
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Journal ArticleDOI

Real-time landmark modelling for visual-guided walking robots

TL;DR: A novel landmark modelling approach to the classification of both the predefined and novelty features in the robot environment is proposed and has been implemented in a quadruped walking robot that has a single camera in its head.
Journal ArticleDOI

Application of neural processing paradigm in visual landmark recognition and autonomous robot navigation

TL;DR: This article addresses the issue of visual landmark recognition in autonomous robot navigation along known routes, by intuitively exploiting the functions of the human visual system and its navigational ability through a feedforward–feedbackward architecture for recognising visual landmarks in real time.
Book ChapterDOI

A vision system for partially occluded landmark recognition

TL;DR: A vision system for extracting and recognising partially occluded 2D visual landmarks that identifies the obscured portions and selectively enhances non-occluded areas of the landmark, while simultaneously suppressing background clutters of the bottom-up edge processed input images.
Proceedings ArticleDOI

A Visual Landmark Recognition System for Autonomous Robot Navigation

TL;DR: A vision system for autonomously guiding a robot along a known route using a single CCD camera, using a memory feedback modulation (MFM) mechanism, which provides a means for the knowledge from the memory to interact and enhance the earlier stages in the system.
References
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Journal ArticleDOI

Human factors and behavioral science: Textons, the fundamental elements in preattentive vision and perception of textures

TL;DR: Preattentive vision serves as an “early warning system” by pointing out those loci of texton differences that should be attended to, according to this theory, at any given instant the visual information intake is relatively modest.
Journal ArticleDOI

Art 2-A: an adaptive resonance algorithm for rapid category learning and recognition

TL;DR: An efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART 2 neural network architecture, but at a speed two to three orders of magnitude faster, which makes practical the use of ART 2 modules in large scale neural computation.
Proceedings ArticleDOI

A visual landmark recognition system for topological navigation of mobile robots

TL;DR: A search algorithm based on genetic techniques for pattern recognition in digital images is presented that allows the topologic localization of a mobile robot using natural and artificial landmarks.
Proceedings ArticleDOI

Using learned visual landmarks for intelligent topological navigation of mobile robots

TL;DR: Practical, high-level topological navigation tasks, making use of the general purpose landmark learning and detection system, which includes the possibility of reading text or icons inside detected landmarks, are presented.
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