Object Selection in Computer Vision: From Multi-thresholding to Percolation Based Scene Representation

2019 ◽  
pp. 161-194
Author(s):  
Vladimir Yu. Volkov ◽  
Mikhail I. Bogachev ◽  
Airat R. Kayumov
Keyword(s):  
Computer Vision ◽  
Object Selection ◽  
Scene Representation

Efficient Object Selection Technique for a Robotized Kitchen

2011 ◽  
Vol 403-408 ◽  
pp. 4873-4879
Author(s):  
Mudit Srivastava ◽  
Anshul Vikram Pandey
Keyword(s):  
Computer Vision ◽  
Robotic Arm ◽  
Rfid Technology ◽  
Disabled People ◽  
Novel Object ◽  
Selection Technique ◽  
Object Selection ◽  
Central Location ◽  
Computer Vision Technology ◽  
Selection Of

This paper proposes a novel object selection technique for a robotized kitchen which provides autonomy to elderly and disabled people while working in kitchen. The interface uses touch screen technology, managed from a central location. The design consists of a robotic arm whose movement is controlled according to the selection of items made by the user. We have used RFID technology for unique identification of the objects and ‘Reverse Code’ for tracking purpose. Based on the response of RFID interrogator and ‘Reverse code’, the robotic arm picks and places the object at the desired location. The interface does not use computer vision technology and provides flexibility with the size of kitchen room. The design also provides several liberalities to the user in context to manual placing and aims at minimizing the errors and rectifying them autonomously to its maximum extent. The arm can also be programmed to select and place various objects required for a particular task, in a predefined manner. At the end of this paper, we have discussed the effectiveness of this system in countering some common errors.

scholarly journals Intelligent Multimodal Framework for Human Assistive Robotics Based on Computer Vision Algorithms

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2408 ◽  
Author(s):  
Eugenio Ivorra ◽  
Mario Ortega ◽  
José Catalán ◽  
Santiago Ezquerro ◽  
Luis Lledó ◽  
...  
Keyword(s):  
Computer Vision ◽  
Pose Estimation ◽  
State Of The Art ◽  
The State ◽  
Assistive Technologies ◽  
Assistive Robotics ◽  
Multimodal Interface ◽  
Persons With Disabilities ◽  
Object Selection ◽  
European Project

Assistive technologies help all persons with disabilities to improve their accessibility in all aspects of their life. The AIDE European project contributes to the improvement of current assistive technologies by developing and testing a modular and adaptive multimodal interface customizable to the individual needs of people with disabilities. This paper describes the computer vision algorithms part of the multimodal interface developed inside the AIDE European project. The main contribution of this computer vision part is the integration with the robotic system and with the other sensory systems (electrooculography (EOG) and electroencephalography (EEG)). The technical achievements solved herein are the algorithm for the selection of objects using the gaze, and especially the state-of-the-art algorithm for the efficient detection and pose estimation of textureless objects. These algorithms were tested in real conditions, and were thoroughly evaluated both qualitatively and quantitatively. The experimental results of the object selection algorithm were excellent (object selection over 90%) in less than 12 s. The detection and pose estimation algorithms evaluated using the LINEMOD database were similar to the state-of-the-art method, and were the most computationally efficient.

Human Vision and Computer Vision

1985 ◽  
Vol 30 (1) ◽  
pp. 47-47
Author(s):  
Herman Bouma
Keyword(s):  
Computer Vision ◽  
Human Vision

Computer vision for industrial applications

1983 ◽  
Vol 2 (5) ◽  
pp. 130
Author(s):  
J.A. Losty ◽  
P.R. Watkins
Keyword(s):  
Computer Vision ◽  
Industrial Applications

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

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