An efficient similarity metric for omnidirectional vision sensors

2006 ◽  
Vol 54 (9) ◽  
pp. 750-757 ◽  
Author(s):  
Emanuele Frontoni ◽  
Primo Zingaretti
Keyword(s):  
Omnidirectional Vision ◽  
Similarity Metric ◽  
Vision Sensors

scholarly journals Using Omnidirectional Vision to Create a Model of the Environment: A Comparative Evaluation of Global-Appearance Descriptors

2016 ◽  
Vol 2016 ◽  
pp. 1-21 ◽  
Author(s):  
L. Payá ◽  
O. Reinoso ◽  
Y. Berenguer ◽  
D. Úbeda
Keyword(s):  
Visual Information ◽  
Comparative Evaluation ◽  
Relevant Information ◽  
Omnidirectional Vision ◽  
Map Building ◽  
Robust Solution ◽  
Robust Model ◽  
Vision Sensors ◽  
Feature Based ◽  
Source Of Information

Nowadays, the design of fully autonomous mobile robots is a key discipline. Building a robust model of the unknown environment is an important ability the robot must develop. Using this model, this robot must be able to estimate its current position and to navigate to the target points. The use of omnidirectional vision sensors is usual to solve these tasks. When using this source of information, the robot must extract relevant information from the scenes both to build the model and to estimate its position. The possible frameworks include the classical approach of extracting and describing local features or working with the global appearance of the scenes, which has emerged as a conceptually simple and robust solution. While feature-based techniques have been extensively studied in the literature, appearance-based ones require a full comparative evaluation to reveal the performance of the existing methods and to tune correctly their parameters. This work carries out a comparative evaluation of four global-appearance techniques in map building tasks, using omnidirectional visual information as the only source of data from the environment.

Real-time human tracking system with multiple omnidirectional vision sensors

2004 ◽  
Vol 35 (2) ◽  
pp. 79-90 ◽  
Author(s):  
Takushi Sogo ◽  
Hiroshi Ishiguro ◽  
Mohan M. Trivedi
Keyword(s):  
Real Time ◽  
Tracking System ◽  
Human Tracking ◽  
Omnidirectional Vision ◽  
Vision Sensors

scholarly journals A State-of-the-Art Review on Mapping and Localization of Mobile Robots Using Omnidirectional Vision Sensors

2017 ◽  
Vol 2017 ◽  
pp. 1-20 ◽  
Author(s):  
L. Payá ◽  
A. Gil ◽  
O. Reinoso
Keyword(s):  
Computer Vision ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Autonomous Vehicles ◽  
Scientific Community ◽  
Mobile Robotics ◽  
State Of The Art ◽  
Omnidirectional Vision ◽  
Vision Sensors ◽  
Source Of Information

Nowadays, the field of mobile robotics is experiencing a quick evolution, and a variety of autonomous vehicles is available to solve different tasks. The advances in computer vision have led to a substantial increase in the use of cameras as the main sensors in mobile robots. They can be used as the only source of information or in combination with other sensors such as odometry or laser. Among vision systems, omnidirectional sensors stand out due to the richness of the information they provide the robot with, and an increasing number of works about them have been published over the last few years, leading to a wide variety of frameworks. In this review, some of the most important works are analysed. One of the key problems the scientific community is addressing currently is the improvement of the autonomy of mobile robots. To this end, building robust models of the environment and solving the localization and navigation problems are three important abilities that any mobile robot must have. Taking it into account, the review concentrates on these problems; how researchers have addressed them by means of omnidirectional vision; the main frameworks they have proposed; and how they have evolved in recent years.

Fast self-localization method for mobile robots using multiple omnidirectional vision sensors

2003 ◽  
Vol 14 (2) ◽  
pp. 129-138 ◽  
Author(s):  
T. Nakamura ◽  
M. Oohara ◽  
T. Ogasawara ◽  
H. Ishiguro
Keyword(s):  
Mobile Robots ◽  
Omnidirectional Vision ◽  
Localization Method ◽  
Vision Sensors
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