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Journal ArticleDOI

A review of log-polar imaging for visual perception in robotics

TLDR
This paper surveys the application of log-polar imaging in robotic vision, particularly in visual attention, target tracking, egomotion estimation, and 3D perception and to help readers identify promising research directions.
About
This article is published in Robotics and Autonomous Systems.The article was published on 2010-04-01. It has received 154 citations till now. The article focuses on the topics: Visual perception & Vision science.

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Citations
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Journal ArticleDOI

Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing

TL;DR: A novel algorithm to identify and classify clouds and cloud shadow, SPARCS: Spatial Procedures for Automated Removal of Cloud and Shadow, is developed, which provides a measure of uncertainty in its classification that can be exploited by other algorithms that require clear sky pixels.
Journal ArticleDOI

Traffic sign recognition using group sparse coding

TL;DR: This paper introduces a new feature learning approach using group sparse coding that outperforms existing coding methods and the obtained results are comparable to the state-of-the-art.
Proceedings ArticleDOI

Robot-centric Activity Recognition from First-Person RGB-D Videos

TL;DR: A framework and algorithm to analyze first person RGBD videos captured from the robot while physically interacting with humans and shows that separating the descriptors extracted from ego-motion and independent motion areas, and using them both, allows the algorithm to achieve superior recognition results.
Journal ArticleDOI

A Taxonomy of Vision Systems for Ground Mobile Robots

TL;DR: A global picture of the state of the art in the area is offered and some promising research lines are discovered, namely in order to respond to the main questions posed when designing robotic vision systems.
References
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Book

Genetic algorithms in search, optimization, and machine learning

TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI

Distinctive Image Features from Scale-Invariant Keypoints

TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.

Genetic algorithms in search, optimization and machine learning

TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book

Genetic Algorithms

Proceedings Article

An iterative image registration technique with an application to stereo vision

TL;DR: In this paper, the spatial intensity gradient of the images is used to find a good match using a type of Newton-Raphson iteration, which can be generalized to handle rotation, scaling and shearing.
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