scholarly journals System that assists the differently abled people

2020 ◽  
pp. 490-493
Author(s):  
Gowri Prasad ◽  
Spandana S ◽  
Poojana V ◽  
Shrinidhi U Kulkarni
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
External Environment ◽  
Human Beings ◽  
Hand Gestures ◽  
Common People ◽  
The Common

All human beings are able to see, listen and interact with their external environment naturally. There are some people who are differently abled and unfortunately they do not have the ability to use their senses to the best extent. Such people are dependent on other means of communication like sign language or hand gestures. As this hinders the communication between the challenged person say bed-ridden or even paralysed and the common people, it affects to a great extent in their progress and makes them difficult to achieve their dreams. To bridge this gap in communication there is a need of system of gesture recognition or sign language.

scholarly journals Computer Vision Based Hand Gesture Recognition For Speech Disabled Persons

2016 ◽  
Vol 11 (1) ◽  
pp. 30-35
Author(s):  
Manoj Acharya ◽  
Dibakar Raj Pant
Keyword(s):  
Neural Network ◽  
Computer Vision ◽  
Sign Language ◽  
Gesture Recognition ◽  
Disabled Persons ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Dependency Analysis ◽  
Hand Gestures

This paper proposes a method to recognize static hand gestures in an image or video where a person is performing Nepali Sign Language (NSL) and translate it to words and sentences. The classification is carried out using Neural Network where contour of the hand is used as the feature. The work is verified successfully for NSL recognition using signer dependency analysis. Journal of the Institute of Engineering, 2015, 11(1): 30-35

scholarly journals HAND GESTURE RECOGNITION FOR INDONESIAN SIGN LANGUAGE INTERPRETER SYSTEM WITH MYO ARMBAND USING SUPPORT VECTOR MACHINE

2020 ◽  
Vol 7 (2) ◽  
pp. 164
Author(s):  
Aditiya Anwar ◽  
Achmad Basuki ◽  
Riyanto Sigit
Keyword(s):  
Support Vector Machine ◽  
Sign Language ◽  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Support Vector ◽  
Hand Gesture ◽  
Deaf People ◽  
Hand Gestures ◽  
Moment Invariant ◽  
Myo Armband

<p><em>Hand gestures are the communication ways for the deaf people and the other. Each hand gesture has a different meaning.  In order to better communicate, we need an automatic translator who can recognize hand movements as a word or sentence in communicating with deaf people. </em><em>This paper proposes a system to recognize hand gestures based on Indonesian Sign Language Standard. This system uses Myo Armband as hand gesture sensors. Myo Armband has 21 sensors to express the hand gesture data. Recognition process uses a Support Vector Machine (SVM) to classify the hand gesture based on the dataset of Indonesian Sign Language Standard. SVM yields the accuracy of 86.59% to recognize hand gestures as sign language.</em></p><p><em><strong>Keywords</strong></em><em>: </em><em>Hand Gesture Recognition, Feature Extraction, Indonesian Sign Language, Myo Armband, Moment Invariant</em></p>

scholarly journals Online Hand Gesture Recognition and Classification for Deaf and Dumb

2021 ◽  
Vol 9 (VI) ◽  
pp. 4402-4404
Author(s):  
U. Mamatha
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Sign Language ◽  
Gesture Recognition ◽  
Reference Image ◽  
Hand Gesture ◽  
Hand Gestures ◽  
Network Layer ◽  
Web Camera ◽  
The Web

As sign language is used by deaf and dumb but the non-sign-language speaker cannot understand there sign language to overcome the problem we proposed this system using python. In this first we taken the some of the hand gestures are captured using the web camera. The image is pre-processed and then feature are extracted from the captured image .comparing the feature extracted image with the reference image. If matched decision is taken the displayed as a text. This helps the non-sign-language members to recognize easily by using Convolutional neural network layer (CNN) with tensor flow

scholarly journals Analisis Penerapan Metode Convex Hull Dan Convexity Defects Untuk Pengenalan Isyarat Tangan

2018 ◽  
Vol 8 (2) ◽  
pp. 105
Author(s):  
Artha Gilang Saputra ◽  
Ema Utami ◽  
Hanif Al Fatta
Keyword(s):  
Convex Hull ◽  
Gesture Recognition ◽  
Recognition System ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Input Device ◽  
Human Beings ◽  
Light Conditions ◽  
Hand Gestures ◽  
Voice Communication

Research of Human Computer Interaction (HCI) and Computer Vision (CV) is increasingly focused on advanced interface for interacting with humans and creating system models for various purposes. Especially for input device problem to interact with computer. Humans are accustomed to communicate with fellow human beings using voice communication and accompanied by body pose and hand gesture. The main purpose of this research is to applying the Convex Hull and Convexity Defects methods for Hand Gesture Recognition system. In this research, the Hand Gesture Recognition system designed with the OpenCV library and then receives input from the user's hand gesture using an integrated webcam on the computer and system generates a language output from the hand-recognizable gestures. Testing involves several variables which affect success in recognizing user's hand gestures, such as hand distance with webcam, corner of the finger, light conditions and background conditions. As a result, the user's hand gestures can be recognized with a stable and accurate when at a distance of 50cm-70cm, corner of the finger 25o–70o, light conditions 150lux-460lux and plain background conditions.

scholarly journals Face and Hand Gesture Recognition System for Controlling VLC Media Player

2021 ◽  
pp. 119-124
Author(s):  
K M Bilvika ◽  
Sneha B K ◽  
Sahana K M ◽  
Tejaswini S M Patil
Keyword(s):  
Computer Vision ◽  
Sign Language ◽  
Gesture Recognition ◽  
Vision Research ◽  
Recognition System ◽  
Hand Gesture ◽  
Hand Gestures ◽  
Media Player ◽  
Language Interpretation ◽  
Intermediate Medium

In human-computer interaction or sign language interpretation, recognizing hand gestures and face detection become predominant in computer vision research. The primary goal of this proposed system is to create a system, which can identify hand gestures and facial detection to convey information for controlling media player. For those who are deaf and dumb sign language is a common, efficient and alternative way for talking, by using the hand and facial gestures we can easily understand them. Here hand and face are directly use as the input to the device for effective communication purpose of gesture identification there is no need of an intermediate medium.

scholarly journals STUDY OF HAND GESTURE RECOGNITION AND CLASSIFICATION

2017 ◽  
Vol 10 (13) ◽  
pp. 25
Author(s):  
Srinivas K ◽  
Manoj Kumar Rajagopal
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
Hand Movement ◽  
Hand Gesture Recognition ◽  
Hand Movements ◽  
Support Vector ◽  
Hand Gesture ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Hand Gestures

To recognize different hand gestures and achieve efficient classification to understand static and dynamic hand movements used for communications.Static and dynamic hand movements are first captured using gesture recognition devices including Kinect device, hand movement sensors, connecting electrodes, and accelerometers. These gestures are processed using hand gesture recognition algorithms such as multivariate fuzzy decision tree, hidden Markov models (HMM), dynamic time warping framework, latent regression forest, support vector machine, and surface electromyogram. Hand movements made by both single and double hands are captured by gesture capture devices with proper illumination conditions. These captured gestures are processed for occlusions and fingers close interactions for identification of right gesture and to classify the gesture and ignore the intermittent gestures. Real-time hand gestures recognition needs robust algorithms like HMM to detect only the intended gesture. Classified gestures are then compared for the effectiveness with training and tested standard datasets like sign language alphabets and KTH datasets. Hand gesture recognition plays a very important role in some of the applications such as sign language recognition, robotics, television control, rehabilitation, and music orchestration.

scholarly journals Design and Development of IoT Device that Recognizes Hand Gestures using Sensors

2021 ◽  
Vol 7 (09) ◽  
pp. 29-34
Author(s):  
Santosh Kumar J, Vamsi, Vinod, Madhusudhan and Tejas
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
Cost Effective ◽  
Physical World ◽  
Internal Resistance ◽  
Hand Gesture ◽  
Hand Gestures ◽  
Digital World ◽  
Custom Made ◽  
Flex Sensors

A hand gesture is a non-verbal means of communication involving the motion of fingers to convey information. Hand gestures are used in sign language and are a way of communication for deaf and mute people and also implemented to control devices too. The purpose of gesture recognition in devices has always been providing the gap between the physical world and the digital world. The way humans interact among themselves with the digital world could be implemented via gestures using algorithms. Gestures can be tracked using gyroscope, accelerometers, and more as well. So, in this project we aim to provide an electronic method for hand gesture recognition that is cost-effective, this system makes use of flex sensors, ESP32 board. A flex sensor works on the principle of change in the internal resistance to detect the angle made by the user’s finger at any given time. The flexes made by hand in different combinations amount to a gesture and this gesture can be converted into signals or as a text display on the screen. A smart glove is designed which is equipped with custom-made flex sensors that detect the gestures and convert them to text and an ESP32 board, the component used to supplement the gestures detected by a flex sensor. This helps in identifying machines the human sign language and perform the task or identify a word through hand gestures and respond according to it.

scholarly journals Menekülés a komplexitástól

Symbolon ◽  
2021 ◽  
Vol 22 (2) ◽  
pp. 7-12
Author(s):  
György Csepeli
Keyword(s):  
Social Media ◽  
Complex Systems ◽  
Human Mind ◽  
Evidence Based ◽  
Inadequate Response ◽  
Human Beings ◽  
Common People ◽  
Symptoms Of Depression ◽  
The Common ◽  
Nature And Society

As a result of the recently occurred pandemic it has become apparent even for the common people that reality no longer can be seen through the lenses of simplification. Humankind has entered a new age characterized by complexity and lack of transparency. The border between nature and society has disappeared revealing that both of them are ruled by laws of complex systems. The relationships in complex systems are non-linear, categories are bond to language and understanding is a function of fuzzy logic. There is one chaordic world where changes cannot be predicted. Sudden small changes can lead to major transformations. The human mind has not been equipped by evolution to the challenges of complexity. Human beings living complexity are driven to escape from insecurity to security. Instead of reducing tension infodemics in social media induce anxiety and a sense of insecurity resulting inadequate response of the users. As a consequence of cognitive inadaptation users of social media tend to develop symptoms of depression, anxiety, paranoia, irrational credulity and resistance to accept evidence-based communications.

Between High Culture and Low Culture; and also The Difference Between Popular Culture and Folk Culture

2019 ◽  
Vol 7 (8) ◽  
pp. 12
Author(s):  
Kunal Debnath
Keyword(s):  
Popular Culture ◽  
Folk Culture ◽  
Common People ◽  
High Culture ◽  
The World ◽  
The Common ◽  
The Difference ◽  
Low Culture

High culture is a collection of ideologies, beliefs, thoughts, trends, practices and works-- intellectual or creative-- that is intended for refined, cultured and educated elite people. Low culture is the culture of the common people and the mass. Popular culture is something that is always, most importantly, related to everyday average people and their experiences of the world; it is urban, changing and consumeristic in nature. Folk culture is the culture of preindustrial (premarket, precommodity) communities.

Current issues in aesthetics and beyond: Revisiting lookism

2020 ◽  
Vol 10 (1-2) ◽  
pp. 59-68
Author(s):  
Peter Takáč
Keyword(s):  
Plastic Surgery ◽  
Social Impact ◽  
Human Beings ◽  
Common View ◽  
Aesthetic Medicine ◽  
Unequal Treatment ◽  
Self Confidence ◽  
Public Status ◽  
The Social ◽  
The Common

AbstractLookism is a term used to describe discrimination based on the physical appearance of a person. We suppose that the social impact of lookism is a philosophical issue, because, from this perspective, attractive people have an advantage over others. The first line of our argumentation involves the issue of lookism as a global ethical and aesthetical phenomenon. A person’s attractiveness has a significant impact on the social and public status of this individual. The common view in society is that it is good to be more attractive and healthier. This concept generates several ethical questions about human aesthetical identity, health, authenticity, and integrity in society. It seems that this unequal treatment causes discrimination, diminishes self-confidence, and lowers the chance of a job or social enforcement for many human beings. Currently, aesthetic improvements are being made through plastic surgery. There is no place on the human body that we cannot improve with plastic surgery or aesthetic medicine. We should not forget that it may result in the problem of elitism, in dividing people into primary and secondary categories. The second line of our argumentation involves a particular case of lookism: Melanie Gaydos. A woman that is considered to be a model with a unique look.

Sign in / Sign up

Export Citation Format

Share Document