Visual Behavior Based Bio-Inspired Polarization Techniques in Computer Vision and Robotics

For long time, it was thought that the sensing of polarization by animals is invariably related to their behavior, such as navigation and orientation. Recently, it was found that polarization can be part of a high-level visual perception, permitting a wide area of vision applications. Polarization vision can be used for most tasks of color vision including object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. The polarization based visual behavior found in the animal kingdom is briefly covered. Then, the authors go in depth with the bio-inspired applications based on polarization in computer vision and robotics. The aim is to have a comprehensive survey highlighting the key principles of polarization based techniques and how they are biologically inspired.

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Bio-Inspired Polarization Vision Techniques for Robotics Applications

Advances in Computational Intelligence and Robotics - Handbook of Research on Advancements in Robotics and Mechatronics ◽

10.4018/978-1-4666-7387-8.ch005 ◽

2015 ◽

pp. 81-117 ◽

Cited By ~ 1

Author(s):

Abd El Rahman Shabayek ◽

Olivier Morel ◽

David Fofi

Keyword(s):

Computer Vision ◽

Autonomous Robots ◽

Light Polarization ◽

Polarization Vision ◽

Animal Kingdom ◽

Biologically Inspired ◽

Distinctive Features ◽

Comprehensive Survey ◽

Common Problems ◽

And Robotics

Researchers have been inspired by nature to build the next generation of smart robots. Based on the mechanisms adopted by the animal kingdom, research teams have developed solutions to common problems that autonomous robots faced while performing basic tasks. Polarization-based behaviour is one of the most distinctive features of some species of the animal kingdom. Light polarization parameters significantly expand visual capabilities of autonomous robots. Polarization vision can be used for most tasks of color vision, like object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. In this chapter, the authors briefly cover polarization-based visual behavior in the animal kingdom. Then, they go in depth with bio-inspired applications based on polarization in computer vision and robotics. The aim is to have a comprehensive survey highlighting the key principles of polarization-based techniques and how they are biologically inspired.

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Bio-Inspired Polarization Vision Techniques for Robotics Applications

Computer Vision ◽

10.4018/978-1-5225-5204-8.ch017 ◽

2018 ◽

pp. 421-457

Author(s):

Abd El Rahman Shabayek ◽

Olivier Morel ◽

David Fofi

Keyword(s):

Computer Vision ◽

Autonomous Robots ◽

Light Polarization ◽

Polarization Vision ◽

Animal Kingdom ◽

Biologically Inspired ◽

Distinctive Features ◽

Comprehensive Survey ◽

Common Problems ◽

And Robotics

Researchers have been inspired by nature to build the next generation of smart robots. Based on the mechanisms adopted by the animal kingdom, research teams have developed solutions to common problems that autonomous robots faced while performing basic tasks. Polarization-based behaviour is one of the most distinctive features of some species of the animal kingdom. Light polarization parameters significantly expand visual capabilities of autonomous robots. Polarization vision can be used for most tasks of color vision, like object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. In this chapter, the authors briefly cover polarization-based visual behavior in the animal kingdom. Then, they go in depth with bio-inspired applications based on polarization in computer vision and robotics. The aim is to have a comprehensive survey highlighting the key principles of polarization-based techniques and how they are biologically inspired.

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Machine Learning Applications in Computer Vision

Image Processing ◽

10.4018/978-1-4666-3994-2.ch045 ◽

2013 ◽

pp. 896-926

Author(s):

Mehrtash Harandi ◽

Javid Taheri ◽

Brian C. Lovell

Keyword(s):

Machine Learning ◽

Computer Vision ◽

Object Recognition ◽

Visual Recognition ◽

Sequential Decision ◽

Biologically Inspired ◽

Transductive Learning ◽

Machine Learning Applications ◽

Appearance Models ◽

Learning Frameworks

Recognizing objects based on their appearance (visual recognition) is one of the most significant abilities of many living creatures. In this study, recent advances in the area of automated object recognition are reviewed; the authors specifically look into several learning frameworks to discuss how they can be utilized in solving object recognition paradigms. This includes reinforcement learning, a biologically-inspired machine learning technique to solve sequential decision problems and transductive learning, and a framework where the learner observes query data and potentially exploits its structure for classification. The authors also discuss local and global appearance models for object recognition, as well as how similarities between objects can be learnt and evaluated.

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Machine Learning Applications in Computer Vision

Machine Learning Algorithms for Problem Solving in Computational Applications ◽

10.4018/978-1-4666-1833-6.ch007 ◽

2012 ◽

pp. 99-132 ◽

Cited By ~ 1

Author(s):

Mehrtash Harandi ◽

Javid Taheri ◽

Brian C. Lovell

Keyword(s):

Machine Learning ◽

Computer Vision ◽

Object Recognition ◽

Visual Recognition ◽

Sequential Decision ◽

Biologically Inspired ◽

Transductive Learning ◽

Machine Learning Applications ◽

Appearance Models ◽

Learning Frameworks

Recognizing objects based on their appearance (visual recognition) is one of the most significant abilities of many living creatures. In this study, recent advances in the area of automated object recognition are reviewed; the authors specifically look into several learning frameworks to discuss how they can be utilized in solving object recognition paradigms. This includes reinforcement learning, a biologically-inspired machine learning technique to solve sequential decision problems and transductive learning, and a framework where the learner observes query data and potentially exploits its structure for classification. The authors also discuss local and global appearance models for object recognition, as well as how similarities between objects can be learnt and evaluated.

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To the memory of the geobotanist. Leonid E. Rodin (to the 100th anniversary of his birthday)

Vegetation of Russia ◽

10.31111/vegrus/2007.10.106 ◽

2007 ◽

pp. 106-107

Author(s):

B. K. Gannibal

Keyword(s):

End Of Life ◽

100Th Anniversary ◽

State University ◽

Botanical Institute ◽

Komarov Botanical Institute ◽

The Future ◽

Long Time ◽

High Level

Leonid Efimovich Rodin (1907-1990) was a graduate of Leningrad state University. To him, the future is known geobotanica, happened to a course in Botanical geography is still at the N. A. Bush. His teachers were also A. P. Shennikov and A. A. Korchagin, who subsequently headed related Department of geobotany and Botanical geography of Leningrad state University. This was the first school scientist. And since the beginning of the 30s of XX century and until the end of life L. E. was an employee of the Department of geobotany of the Komarov Botanical Institute (RAS), where long time worked together with E. M. Lavrenko, V. B. Sochava, B. A. Tikhomirov, V. D. Alexandrova and many other high-level professionals, first continuing to learn and gain experience, then defining the direction of development of geobotany in the Institute and the country as a whole.

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Computer Vision and robotics in postal automation

Human Systems Management ◽

10.3233/hsm-1999-183-411 ◽

1999 ◽

Vol 18 (3-4) ◽

pp. 265-273

Author(s):

Giovanni B. Garibotto

Keyword(s):

Image Processing ◽

Computer Vision ◽

Pattern Recognition ◽

Material Handling ◽

State Of The Art ◽

Short Description ◽

The Other ◽

Functional Requirements ◽

Postal Automation ◽

And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

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Corticobasal Degeneration Misdiagnosed As Musculoskeletal Disease: A Challenging Diagnosis of Higher-Level Gait Disease

Journal of Neurosciences in Rural Practice ◽

10.1055/s-0040-1716773 ◽

2020 ◽

Vol 11 (04) ◽

pp. 640-642

Author(s):

Halil Onder

Keyword(s):

Corticobasal Degeneration ◽

The Elderly ◽

Gait Disorders ◽

Physiological Changes ◽

Gait Abnormality ◽

Age Related ◽

Musculoskeletal Problems ◽

Neurological Exam ◽

Long Time ◽

High Level

AbstractGait disorders are common in the elderly as there are various causes of neurological and non-neurological conditions. On the other hand, most of the gait parameters do change with advancing age which is identified as age-related physiological changes in gait. At this point, the discrimination between age-related physiological changes and gait disorders may be strictly challenging. After identifying gait as an abnormal pattern, classification of it and making the responsible pathophysiology also require high-level expertise in this regard. Herein, we present a rare patient with corticobasal degeneration (CBD) who had admitted initially due to complaints of gait problems. Over a long time, the patient had received the misdiagnosis of gait abnormality due to musculoskeletal problems by multiple physicians. However, the detailed neurological exam showed a higher level gait disorder (HLGD). Further investigations at this point yielded the diagnosis of CBD.

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