Iterative Design of Sonification Techniques to Support People with Visual Impairments in Obstacle Avoidance

2021 ◽  
Vol 14 (4) ◽  
pp. 1-27
Author(s):  
Giorgio Presti ◽  
Dragan Ahmetovic ◽  
Mattia Ducci ◽  
Cristian Bernareggi ◽  
Luca A. Ludovico ◽  
...  
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Mobile App ◽  
Independent Mobility ◽  
Listening Tests ◽  
Recent Computer ◽  
Computer Vision Technology ◽  
White Cane ◽  
Real Time Information

Obstacle avoidance is a major challenge during independent mobility for blind or visually impaired (BVI) people. Typically, BVI people can only perceive obstacles at a short distance (about 1 m, in case they are using the white cane), and some obstacles are hard to detect (e.g . , those elevated from the ground), or should not be hit by the white cane (e.g . , a standing person). A solution to these problems can be found in recent computer-vision techniques that can run on mobile and wearable devices to detect obstacles at a distance. However, in addition to detecting obstacles, it is also necessary to convey information about them in real time. This contribution presents WatchOut , a sonification technique for conveying real-time information about the main properties of an obstacle to a BVI person, who can then use this additional feedback to safely navigate in the environment. WatchOut was designed with a user-centered approach, involving four iterations of online listening tests with BVI participants in order to define, improve and evaluate the sonification technique, eventually obtaining an almost perfect recognition accuracy. WatchOut was also implemented and tested as a module of a mobile app that detects obstacles using state-of-the-art computer vision technology. Results show that the system is considered usable and can guide the users to avoid more than 85% of the obstacles.

Computer vision technology for real-time food quality assurance during drying process

2014 ◽  
Vol 39 (1) ◽  
pp. 76-84 ◽  
Author(s):  
Mortaza Aghbashlo ◽  
Soleiman Hosseinpour ◽  
Mahdi Ghasemi-Varnamkhasti
Keyword(s):  
Computer Vision ◽  
Quality Assurance ◽  
Real Time ◽  
Food Quality ◽  
Drying Process ◽  
Computer Vision Technology

scholarly journals A Computer Vision-Based Real-Time Load Perception Method for Belt Conveyors

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Mengchao Zhang ◽  
Manshan Zhou ◽  
Hao Shi
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Conveyor Belt ◽  
Conveyor System ◽  
Load Detection ◽  
Speed Regulation ◽  
Computer Vision Technology ◽  
Belt Conveyors ◽  
Energy Saving Control ◽  
Load Perception

Real-time load detection method for belt conveyors based on computer vision is the research topic of this paper. A belt conveyor system equipped with cameras and a laser generator is used as the test apparatus. As the basis for conveyor intelligent speed regulation, two methods from different angles to perceive the load of conveyor belt were proposed, applied, and compared in this paper. Method 1 is based on the area proportion and method 2 is the detection based on laser-based computer vision technology. Laboratory experiments show that both methods can well detect the load on the conveyor belt. Method 2 is more economical and practical under the background of existing technology, also compared to the method 1, which provides a new idea and theoretical basis for the energy-saving control and intelligent development of the conveyor.

scholarly journals Real Time Tracking RGB Color Based Kinect

2017 ◽  
Vol 11 (3) ◽  
pp. 98
Author(s):  
Ahmed Mustafa Taha Alzbier ◽  
Hang Cheng
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Video Processing ◽  
Background Subtraction ◽  
Moving Objects ◽  
Blue Color ◽  
The Real ◽  
Color Recognition ◽  
Kinect Camera ◽  
Computer Vision Technology

As the present computer vision technology is growing up, and the multiple RGB color object tracking is considered as one of the important tasks in computer vision and technique that can be used in many applications such as surveillance in a factory production line, event organization, flow control application, analysis and sort by colors and etc. In video processing applications, variants of the background subtraction method are broadly used for the detection of moving objects in video sequences. The background subtraction is the most popular and common approach for motion detection. However , this is paper presents our investigation the first objective of the whole algorithm chain is to find the RGB color within a video. The idea from the beginning was to look for certain specific features of the patches, which would allow distinguishing red, green and blue color objects in the image. In this paper an algorithm is proposed to track the real time moving RGB color objects using kinect camera. We will use a kinect camera to capture the real time video and making an image frame from this video and extracting red, green and blue color .Here image processing is done through MATLAB for color recognition process each color. Our method can tracking accurately at 95% in real-time.

Design of Robot Lawn Mower Based on Computer Vision

2013 ◽  
Vol 404 ◽  
pp. 624-630
Author(s):  
Fa Yu Wang ◽  
Zhen Li Gao ◽  
Hong Yu Yin
Keyword(s):  
Computer Vision ◽  
Edge Detection ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Path Tracking ◽  
Processing Algorithm ◽  
Lawn Mower ◽  
Boundary Characteristics ◽  
New Research

In this paper, we introduce a new research about mowing robot on obstacle avoidanceand path tracking controlling theoretically and practically, and propose the mowing control methodwhich based on computer vision. Lawn images collected by camera, through the extraction ofprogramming dealing with lawn, obstacles and boundary characteristics to achieve edge separation.Through special processing algorithm to determine boundary arises and obstacles location, size andspeed of the robot, with real-time capturing and processing. This paper gives the complete imagerecognition processing, and analyzes several methods of image filtering and edge detection, andproposes simple control algorithm for obstacle avoidance, and applies MATLAB for obstacleavoidance simulation. The results show that: the method can correctly identify the obstacles andboundaries, through the output about location, size of the obstacles and boundary, border slope andspeed of the robot to control robot mower. Most importantly, that computer vision applying in themowing robot itself is an innovation.

scholarly journals PSIXPORT: Mobile App for Ecological Momentary Assessment of Psychological Dimensions in Sport Injury

2021 ◽  
Vol 12 ◽  
Author(s):  
Luis J. González-Barato ◽  
Víctor J. Rubio ◽  
José Manuel Hernández ◽  
Iván Sánchez-Iglesias
Keyword(s):  
Real Time ◽  
Cognitive Appraisals ◽  
Mobile App ◽  
Accurate Information ◽  
Psychological Variables ◽  
Rehabilitation Process ◽  
Ecological Momentary ◽  
Real Time Information ◽  
Time Information ◽  
Injured Athletes

Retrospective self-reports have been commonly used to assess psychological variables such as feelings, thoughts, or emotions. Nevertheless, this method presents serious limitations to gather accurate information about variables that change over time. The Ecological Momentary Assessment (EMA) approach has been used to deal with some of the limitations these retrospective assessment methods present, and for gathering real-time information about dynamic psychological variables, such as feelings, thoughts, or behaviors. In the sports injury rehabilitation context, athletes' thoughts, feelings, behaviors, and pain perceptions during the rehabilitation process can influence the outcomes of this process. These responses change over different stages of the rehabilitation and taking them into account can help therapists to adapt the rehabilitation process and increasing their effectiveness. With this aim, an EMA mobile app (PSIXPORT) was designed to gather real-time information about severely injured athletes' cognitive appraisals, emotional responses, behaviors, and pain perceptions during their rehabilitation process. The goals of this study were to evaluate Psixport's ability to gather real-time information about injured athletes' psychological responses during the rehabilitation, to test the users' perceived usability of Psixport, and to compare the reliability and differences between real-time data gathered with Psixport and the data gathered through the one-time retrospective method. Twenty-eight severely injured athletes (10 men and 18 women) were assessed using Psixport, a retrospective questionnaire, and the uMARS usability test. Results showed that Psixport can be considered as a good tool to gather information about injured athletes' cognitive appraisals, emotional responses, behaviors, and pain perceptions. Moreover, multiple data assessments gathered with the app showed to be more accurate information about injured athletes' psychological responses than one-time retrospective reports.

Measurement of Work Piece Surface Quality Based on Digital Image Processing

2011 ◽  
Vol 101-102 ◽  
pp. 689-692
Author(s):  
Cheng Yu Wu ◽  
Fei Qing Wu ◽  
Hui Mei Yang
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Real Time ◽  
Surface Quality ◽  
Digital Image Processing ◽  
Digital Image ◽  
Surface Flaw ◽  
Work Piece ◽  
Computer Vision Technology ◽  
Modern Image

This article discusses how to apply sensor mixture, modern image handle and computer vision technology to analyse and to deal with the feature messages of the ground work piece surface flaw, and computer how to apply the filtered feature messages to identify these flaws. Result shows that this system can find the defect work piece real time from the images for testing.

scholarly journals Efficient Path Planning Method of USV for Intelligent Target Search

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
Jing Zhang ◽  
Fan Zhang ◽  
Zengyuan Liu ◽  
Yunsong Li
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Prior Information ◽  
Planning Method ◽  
Target Search ◽  
Global Path Planning ◽  
Local Path ◽  
Real Time Information ◽  
Time Information

AbstractIn order to accomplish a target search task safely and efficiently and make full use of prior information and real-time information, a path planning method of unmanned surface vehicle (USV) for intelligent target search is proposed. The overall strategy is divided into three parts: global path planning based on prior information, local path planning based on real-time information, and improved A* obstacle avoidance algorithm. Before the start of the task, the global path planning is carried out based on prior information such as the initial position of USV, the predicted position of the target and range of search area. After the start of the task, if USV finds suspicious targets, in order to further approach these suspicious targets, it will enter different local path planning modes according to the characteristics of these targets. During task execution, if obstacles are encountered, an improved A* obstacle avoidance algorithm is adopted. The simulation results show that the proposed method can improve the efficiency of target recognition and reduce the turning cost of USV when encountering obstacles. So, for USV intelligent target search, the proposed path planning method can save resources and improve search efficiency.

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