A comprehensive survey on computer vision based concepts, methodologies, analysis and applications for automatic gun/knife detection

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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A comprehensive survey on computer vision based approaches for automatic identification of products in retail store

Image and Vision Computing ◽

10.1016/j.imavis.2019.03.005 ◽

2019 ◽

Vol 86 ◽

pp. 45-63 ◽

Cited By ~ 4

Author(s):

Bikash Santra ◽

Dipti Prasad Mukherjee

Keyword(s):

Computer Vision ◽

Retail Store ◽

Automatic Identification ◽

Comprehensive Survey

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A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision

Sensors ◽

10.3390/s20092641 ◽

2020 ◽

Vol 20 (9) ◽

pp. 2641 ◽

Cited By ~ 3

Author(s):

Anca Morar ◽

Alin Moldoveanu ◽

Irina Mocanu ◽

Florica Moldoveanu ◽

Ion Emilian Radoi ◽

...

Keyword(s):

Computer Vision ◽

Augmented Reality ◽

Object Tracking ◽

Indoor Localization ◽

New Classification ◽

Localization Method ◽

Localization Domain ◽

Mobile Cameras ◽

Comprehensive Survey ◽

Orientation Information

Computer vision based indoor localization methods use either an infrastructure of static cameras to track mobile entities (e.g., people, robots) or cameras attached to the mobile entities. Methods in the first category employ object tracking, while the others map images from mobile cameras with images acquired during a configuration stage or extracted from 3D reconstructed models of the space. This paper offers an overview of the computer vision based indoor localization domain, presenting application areas, commercial tools, existing benchmarks, and other reviews. It provides a survey of indoor localization research solutions, proposing a new classification based on the configuration stage (use of known environment data), sensing devices, type of detected elements, and localization method. It groups 70 of the most recent and relevant image based indoor localization methods according to the proposed classification and discusses their advantages and drawbacks. It highlights localization methods that also offer orientation information, as this is required by an increasing number of applications of indoor localization (e.g., augmented reality).

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A Systematic Review on Data Scarcity Problem in Deep Learning: Solution and Applications

ACM Computing Surveys ◽

10.1145/3502287 ◽

2022 ◽

Author(s):

Ms. Aayushi Bansal ◽

Dr. Rewa Sharma ◽

Dr. Mamta Kathuria

Keyword(s):

Neural Networks ◽

Computer Vision ◽

Deep Learning ◽

Language Processing ◽

Data Augmentation ◽

Medical Science ◽

Real Life ◽

Survey Paper ◽

Augmentation Techniques ◽

Comprehensive Survey

Recent advancements in deep learning architecture have increased its utility in real-life applications. Deep learning models require a large amount of data to train the model. In many application domains, there is a limited set of data available for training neural networks as collecting new data is either not feasible or requires more resources such as in marketing, computer vision, and medical science. These models require a large amount of data to avoid the problem of overfitting. One of the data space solutions to the problem of limited data is data augmentation. The purpose of this study focuses on various data augmentation techniques that can be used to further improve the accuracy of a neural network. This saves the cost and time consumption required to collect new data for the training of deep neural networks by augmenting available data. This also regularizes the model and improves its capability of generalization. The need for large datasets in different fields such as computer vision, natural language processing, security and healthcare is also covered in this survey paper. The goal of this paper is to provide a comprehensive survey of recent advancements in data augmentation techniques and their application in various domains.

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

Image Processing ◽

10.4018/978-1-4666-3994-2.ch072 ◽

2013 ◽

pp. 1463-1491

Author(s):

Abd El Rahman Shabayek ◽

Olivier Morel ◽

David Fofi

Keyword(s):

Computer Vision ◽

Object Recognition ◽

Visual Perception ◽

Polarization Vision ◽

Visual Behavior ◽

Biologically Inspired ◽

Long Time ◽

Comprehensive Survey ◽

High Level ◽

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.

Download Full-text

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.

Download Full-text