• Proceedings of the KIEE Conference
• /
• 2007.04a
• /
• pp.216-218
• /
• 2007

Korean Sign Language (KSL) is a communication method for the Deaf in Korea, and hand shape is one of important elements in sign language. In this paper, we developed a KSL hand shape editor to simply compose hand shape and connect it to a database. We can edit hand shape by a graphical user interface (GUI) on 3D virtual reality environment. Hand shape codes are connected to a sign word editor to synthesize sign motion and to decrease total amount of KSL data.

• Journal of Digital Contents Society
• /
• v.10 no.2
• /
• pp.319-326
• /
• 2009

In this paper, we present an algorithm which recognize hand shape in real time using only image without adhering separate sensor. Hand recognizes using edge orientation histogram, which comes under a constant quantity of 2D appearances because hand shape is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantity, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis(PCA) method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Human interface system manufacture technique, which controls a home electric appliance or game using, suggested method at experience could be applied.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.911-914
• /
• 2011

Detecting Hand Region is essencial technology to providing User based interface and many research has been continue. In this paper will propose Hand Region Detection method by using HSV space based on Back Projection and Hand Shape Recognition using Hu Moment. By using Back Projection, I updated reliability on Hand Region Detection by Back Projection method and, Confirmed Hand Shape could be recognized through Hu moment.

• Journal of Broadcast Engineering
• /
• v.18 no.3
• /
• pp.393-400
• /
• 2013

Hand shape recognition is a fundamental technique for implementing natural human-computer interaction. In this paper, we discuss a method for effectively detecting a hand region in Kinect-based hand shape recognition. Since Kinect is a camera that can capture color images and infrared images (or depth images) together, both images can be exploited for the process of detecting a hand region. That is, a hand region can be detected by finding pixels having skin colors or by finding pixels having a specific depth. Therefore, after analyzing the performance of each, we need a method of properly combining both to clearly extract the silhouette of hand region. This is because the hand shape recognition rate depends on the fineness of detected silhouette. Finally, through comparison of hand shape recognition rates resulted from different hand region detection methods in general environments, we propose a high-performance hand region detection method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.9
• /
• pp.3924-3940
• /
• 2020

Dynamic hand gesture recognition(d-HGR) plays an important role in human-computer interaction(HCI) system. With the growth of hand-pose estimation as well as 3D depth sensors, depth, and the hand-skeleton dataset is proposed to bring much research in depth and 3D hand skeleton approaches. However, it is still a challenging problem due to the low resolution, higher complexity, and self-occlusion. In this paper, we propose a hand-shape feature extraction(HSFE) network to produce robust hand-shapes. We build a hand-shape model, and hand-skeleton based on LSTM to exploit the temporal information from hand-shape and motion changes. Fusion between two models brings the best accuracy in dynamic hand gesture (DHG) dataset.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.4
• /
• pp.34-40
• /
• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.45 no.5
• /
• pp.758-769
• /
• 2021

Today, functional gloves must allow the wearer to perform many kinds of delicate work while protecting the hands from hazardous materials. In this study, multiple analyses of 3D hand measurements were performed to provide information on the hand size and shape required for the design of functional gloves for adult men. Size and shape characteristics were identified from 19 different hand measurements, and three factors were collected through factor analysis. The aggregated factor score was used to classify men's hand shapes into three types. These types showed different distribution patterns according to age, indicating a significant distribution difference between hand type and age group. Discriminant analysis extracted nine items that highly contributed to determining hand type. However, since the data provided by Size Korea have some limitations in fully representing hand shape, sampling additional types of hand measurements and using consistent conditions and methods are required for more accurate analysis.

• Proceedings of the Korea Contents Association Conference
• /
• 2006.11a
• /
• pp.801-805
• /
• 2006

In this paper, we describe a system of controlling the pictorial puzzle program using information of hand shape. We extract hand region using skin color information and then principal component analysis uses centroidal profile information which comes blob of 2D appearance for hand shape recognition. This method suit hand shape recognition in real time because it extracts hand region accurately, has little computation quantity, and is less sensitive to lighting change using skin color information in complicated background. Finally, we controlled a pictorial puzzle with using recognized hand shape information. This method has good result when we make an experiment on application of pictorial puzzle. Besides, it can use so many HCI field.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.44 no.4 s.316
• /
• pp.48-54
• /
• 2007

Hand shape is one of important elements in Korean Sign Language (KSL), which is a communication method for the deaf. To express sign motion in a virtual reality environment based on OpenGL, we need an editor which can insert and modify sign motion data. However, it is very difficult that people, who lack knowledge of sign 1anguage, exactly edit and express hand shape using the existing editors. We also need a program to efficiently construct and store the hand shape data because the number of data is very large in a sign word dictionary. In this paper we developed a KSL hand shape editor to easily construct and edit hand shape by a graphical user interface (GUI), and to store it in a database. Hand shape codes are used in a sign word editor to synthesize sign motion and decreases total amount of KSL data.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.28 no.910
• /
• pp.1300-1311
• /
• 2004

The aim of this study was to provide the 2 and 3 dimensional statistics requisite in the sizing system and design of gloves. The 64 2-dimensional static measurements were selected to provide information about hands. Participants in the study were 824 adults, aged between 18 and 64. To summarize the information from the measurement values, a Factor Analysis and a Cluster Analysis among multivariate analyses were performed. 3-D scanner was used for visual results of hand shape of each cluster. The results were as follows. Twenty-two items were used for the factor and cluster analysis in order to classify the adult hand shape. The variable quantities that are explained by a total of 3 factors amounted to under 79.37% of the variable quantities. The definition results of the factors related to the hands are as follows: Factor 1 is the horizontal dimension, the thickness of hand factor; Factor 2 is the height of the crotch; and Factor 3 is the vertical dimension of the hand. The adults' group hand was divided into 2 clusters according to a cluster analysis using factor scores. The characteristics according to hand type were as follows: Cluster 1 referred to high horizontal dimensions and thickness, rather small vertical dimensions and crotch height; and Cluster 2 represented the rather smaller horizontal dimensions and thickness but longer hand length than Type 1. To provide specific shape data of each cluster, 3-D scanner measurement was performed. 3-dimensional data base was developed for each cluster type and visual information was provided.