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This paper proposes a novel sign language learning system based on 2D image sampling and concatenating to solve the problems of conventional sign recognition. The system constructs the training data by sampling and concatenating from a sign language demonstration video at a certain sampling rate. The learning process is implemented with a well-known network, convolutional neural network. 6 sign language...
In the followed article is presented a program able to make gesture image recognition, it is capable to identify each one letter of alphabet. The developments objective is make possible any person can be able to understand and by self-learning to get acknowledge the signal language.
Sign language is widely used by individuals with hearing impairment to communicate with each other conveniently using hand gestures. However, non-sign-language speakers find it very difficult to communicate with those with speech or hearing impairment since it interpreters are not readily available at all times. Many countries have their own sign language, such as American Sign Language (ASL) which...
In the past years, the recognition of gesture feature has been glamoured attention as a natural human. The communication system can build the human relationships. The mode of communication will be verbal and non-verbal. The non-verbal communication is not only used for the physically challenged person, but also used in gaming, surveying, etc. There is no need of peripheral device to interact with...
Recognizing sign language is an important interest area since there are many speech and hearing impaired people in the world. They need to be understood by other people and understand them as well. Unfortunately, the number of people who have the knowledge of sign language is not many. In order to communicate with handicapped people, existence of some automatized systems may be helpful. Therefore,...
The following topics are dealt with: Imaging for remote sensing; computer vision; brain MRI segmentation; object class recognition; anomaly detection in spectral imaging; JAB to RGB multidimensional lookup tables; print engine color management; camera pose determination; hierarchical image clustering for analyzing eye tracking; blind cluster multispectral satellite imagery and; studying human preferences...
This article focuses on the development of computational methods and software for the computerized real-time Ukrainian sign language recognition system. The proposed recognition model differs from known approaches in the identification of hand shape in motion. The system makes use of a video camera as a sensor. Hand shape recognition method based on fingertips location and pseudo 2-dimentional image...
We present a novel and robust system for recognizing two handed motion based gestures performed within continuous sequences of sign language. While recognition of valid sign sequences is an important task in the overall goal of machine recognition of sign language, detection of movement epenthesis is important in the task of continuous recognition of natural sign language. We propose a framework for...
We propose a novel approach for solving the Chinese manual alphabet in vision. Rather than focusing on local features and their consistencies in the images data, our approach aims at extracting both the global and local features of an image. Features calculated from gray-level co-occurrence matrix and other multi-features are introduced for the classifier to characterize the various visual properties...
This paper presents detailed description of a real-time hand gesture recognition system using embedded DSP board and image processing approaches. Such a system which can identify hand postures and dynamic gestures has manifold potential applications range from sign languages to human computer interaction. We use Q6455 DSP board based on 4 TI-TMS320C6455 DSPs as the computational unit. This versatile...
Sign language is the most natural and expressive way for the hearing impaired. Its most appealing application is the development of more effective and friendly interfaces for human-machine interaction. Gestures are a natural and powerful way of communication. A hand gesture recognition system can provide an opportunity for a mute person to communicate with normal people without the need of an interpreter...
Nowadays, sign language is commonly used as a communication language for auditory handicapped people. In addition to voice and controller pads, hand gestures can also be an effective way of communication between humans and robots or even between auditory handicapped people and robots. To be an effective sign recognition system, it should be glove-free, fast, small database and accurate. In this project,...
We have developed a prototype for a learning environment for deaf and hard of hearing children. This demonstration consists of hands-on experience with the prototype. In total, there are three exercises: 1) an introduction of all pictures and corresponding signs, 2) multiple choice sign-to-picture and 3) performing the sign that corresponds to the picture shown on the screen. The live recognition...
Human hand detection problem has important applications in sign language and human machine interfaces. In this work, we present a novel approach for learning a vision-based hand detection system. The main contribution is a robust on-line boosting-based framework for real-time detection of a hand in unconstrained environments. The use of efficient representative features allows fast computation while...
Sign language is complex visual-spatial language most used in deaf society, and is a representative example of hand gesture with linguistic structure. Korean manual alphabet is a manual alphabet that augments the vowel and consonant of Korean sign language. This paper presents a system which recognizes the Korean manual alphabet (KMA) using a USB camera and translates into a normal Korean character...
In this paper an approach to classify hand shapes into different classes according to the similarity measures between features is proposed. We show how to use an Exploratory Data Analysis to extract novel, single feature of hand from images. Based on the obtained curve-like shape of the feature, hands are classified into one of 21 possible classes of Croatian sign language using Dynamic Time Warping...
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