• Title/Summary/Keyword: gesture matching

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A Framework for 3D Hand Gesture Design and Modeling (삼차원 핸드 제스쳐 디자인 및 모델링 프레임워크)

  • Kwon, Doo-Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.10
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    • pp.5169-5175
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    • 2013
  • We present a framework for 3D hand gesture design and modeling. We adapted two different pattern matching techniques, Dynamic Time Warping (DTW) and Hidden Markov Models (HMMs), to support the registration and evaluation of 3D hand gestures as well as their recognition. One key ingredient of our framework is a concept for the convenient gesture design and registration using HMMs. DTW is used to recognize hand gestures with a limited training data, and evaluate how the performed gesture is similar to its template gesture. We facilitate the use of visual sensors and body sensors for capturing both locative and inertial gesture information. In our experimental evaluation, we designed 18 example hand gestures and analyzed the performance of recognition methods and gesture features under various conditions. We discuss the variability between users in gesture performance.

Real-time hand tracking and recognition based on structured template matching (구조적 템플렛 매칭에 기반을 둔 실시간 손 추적 및 인식)

  • Kim, Song-Gook;Bae, Ki-Tae;Lee, Chil-Woo
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.1037-1043
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    • 2006
  • 본 논문에서는 유비쿼터스 컴퓨팅 오피스 환경에서 가장 직관적인 HCI 수단인 손 제스처를 사용하여 대형 스크린 상의 응용 프로그램들을 쉽게 제어할 수 있는 시스템을 제안한다. 손 제스처는 손 영역의 정보, 손 중심점의 위치 변화값과 손가락 형상을 이용하여 시스템 제어에 필요한 종류들을 미리 정의해 둔다. 먼저 효율적으로 손 영역 획득을 위해 적외선 카메라를 사용하여 연속된 영상을 획득한다. 획득된 영상 프레임으로부터 구조적 템플레이트 매칭 방법을 사용하여 손의 중심(centroid) 및 손가락끝(fingertip)을 검출한다. 인식과정에서는 양손의 Euclidean distance와 손가락 형상 정보를 이용하여 미리 정의된 제스처와 비교하여 인식을 행한다. 본 논문에서 제안한 비전 기반 hand gesture 제어 시스템은 인간과 컴퓨터의 상호작용을 이해하는데 많은 이점을 제공할 수 있다. 실험 결과를 통해 본 논문에서 제안한 방법의 효율성을 입증한다.

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Alphabetical Gesture Recognition using HMM (HMM을 이용한 알파벳 제스처 인식)

  • Yoon, Ho-Sub;Soh, Jung;Min, Byung-Woo
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.384-386
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    • 1998
  • The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interaction(HCI). Many methods hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network(NN), Hidden Markov Model(HMM) and so on. In our research, a HMMs is proposed for alphabetical hand gesture recognition. In the preprocessing stage, the proposed approach consists of three different procedures for hand localization, hand tracking and gesture spotting. The hand location procedure detects the candidated regions on the basis of skin-color and motion in an image by using a color histogram matching and time-varying edge difference techniques. The hand tracking algorithm finds the centroid of a moving hand region, connect those centroids, and thus, produces a trajectory. The spotting a feature database, the proposed approach use the mesh feature code for codebook of HMM. In our experiments, 1300 alphabetical and 1300 untrained gestures are used for training and testing, respectively. Those experimental results demonstrate that the proposed approach yields a higher and satisfying recognition rate for the images with different sizes, shapes and skew angles.

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Palm Area Detection by Maximum Hand Width (손 최장너비 기반 손바닥 영역 검출)

  • Choi, Eun Chang;Kim, Jun Yeon;Lee, Jae Won;Lim, Jong Gwan
    • The Journal of the Korea Contents Association
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    • v.18 no.4
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    • pp.398-405
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    • 2018
  • In the HCI, hand gesture recognition is attracting attention as a method for interaction and information exchange between users and devices along with the development of IT devices. In hand gesture recognition through image processing, palm region detection is a key process contributing to improvement of processing speed and recognition rate. In this paper, we propose a new method for image segmentation between the hand and wrist for palm area detection. The anatomical characteristics of the hand are used to calculate the distance between the iliac bones of the thumb and little finger, which have the widest width, by the horizontal projection histogram of the hand image, and then the palm area is detected by drawing a circle having the width as the diameter. In order to verify the superiority of this method, multiple stage template matching is used to compare and evaluate recognition performance against the four conventional methods for 10 hand gestures. Note that the literatures to offer palm area detection performance evaluation are few although there are many studies on hand gesture recognition.

A Study on Hand Gesture Recognition with Low-Resolution Hand Images (저해상도 손 제스처 영상 인식에 대한 연구)

  • Ahn, Jung-Ho
    • Journal of Satellite, Information and Communications
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    • v.9 no.1
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    • pp.57-64
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    • 2014
  • Recently, many human-friendly communication methods have been studied for human-machine interface(HMI) without using any physical devices. One of them is the vision-based gesture recognition that this paper deals with. In this paper, we define some gestures for interaction with objects in a predefined virtual world, and propose an efficient method to recognize them. For preprocessing, we detect and track the both hands, and extract their silhouettes from the low-resolution hand images captured by a webcam. We modeled skin color by two Gaussian distributions in RGB color space and use blob-matching method to detect and track the hands. Applying the foodfill algorithm we extracted hand silhouettes and recognize the hand shapes of Thumb-Up, Palm and Cross by detecting and analyzing their modes. Then, with analyzing the context of hand movement, we recognized five predefined one-hand or both-hand gestures. Assuming that one main user shows up for accurate hand detection, the proposed gesture recognition method has been proved its efficiency and accuracy in many real-time demos.

Mobile Gesture Recognition using Dynamic Time Warping with Localized Template (지역화된 템플릿기반 동적 시간정합을 이용한 모바일 제스처인식)

  • Choe, Bong-Whan;Min, Jun-Ki;Jo, Seong-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.4
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    • pp.482-486
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    • 2010
  • Recently, gesture recognition methods based on dynamic time warping (DTW) have been actively investigated as more mobile devices have equipped the accelerometer. DTW has no additional training step since it uses given samples as the matching templates. However, it is difficult to apply the DTW on mobile environments because of its computational complexity of matching step where the input pattern has to be compared with every templates. In order to address the problem, this paper proposes a gesture recognition method based on DTW that uses localized subset of templates. Here, the k-means clustering algorithm is used to divide each class into subclasses in which the most centered sample in each subclass is employed as the localized template. It increases the recognition speed by reducing the number of matches while it minimizes the errors by preserving the diversities of the training patterns. Experimental results showed that the proposed method was about five times faster than the DTW with all training samples, and more stable than the randomly selected templates.

An Implementation of Taekwondo Action Recognition System using Multiple Sensing (멀티플 센싱을 이용한 태권도 동작 인식 시스템 구현)

  • Lee, Byong Kwon
    • Journal of Korea Multimedia Society
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    • v.19 no.2
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    • pp.436-442
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    • 2016
  • There are a lot of sports when you left the victory and the defeat of the match the referee subjective judgment. In particular, TaeKwonDo pumse How accurate a given action? Is important. Objectively evaluate the subjective opinion of victory and defeat in a sporting event and the technology to keep as evidence is required. This study was implemented a system for recognizing Taekwondo executed through the number of motion recognition device. Step Sensor also used to detect a user's location. This study evaluated the rate matching the standard gesture data and the motion data. Through multiple gesture recognition equipment was more accurate assessment of the Taekwondo action.

Recognizing Human Facial Expressions and Gesture from Image Sequence (연속 영상에서의 얼굴표정 및 제스처 인식)

  • 한영환;홍승홍
    • Journal of Biomedical Engineering Research
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    • v.20 no.4
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    • pp.419-425
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    • 1999
  • In this paper, we present an algorithm of real time facial expression and gesture recognition for image sequence on the gray level. A mixture algorithm of a template matching and knowledge based geometrical consideration of a face were adapted to locate the face area in input image. And optical flow method applied on the area to recognize facial expressions. Also, we suggest hand area detection algorithm form a background image by analyzing entropy in an image. With modified hand area detection algorithm, it was possible to recognize hand gestures from it. As a results, the experiments showed that the suggested algorithm was good at recognizing one's facial expression and hand gesture by detecting a dominant motion area on images without getting any limits from the background image.

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Design and Implementation for Korean Character and Pen-gesture Recognition System using Stroke Information (획 정보를 이용한 한글문자와 펜 제스처 인식 시스템의 설계 및 구현)

  • Oh, Jun-Taek;Kim, Wook-Hyun
    • The KIPS Transactions:PartB
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    • v.9B no.6
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    • pp.765-774
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    • 2002
  • The purpose of this paper is a design and implementation for korean character and pen-gesture recognition system in multimedia terminal, PDA and etc, which demand both a fast process and a high recognition rate. To recognize writing-types which are written by various users, the korean character recognition system uses a database which is based on the characteristic information of korean and the stroke information Which composes a phoneme, etc. In addition. it has a fast speed by the phoneme segmentation which uses the successive process or the backtracking process. The pen-gesture recognition system is performed by a matching process between the classification features extracted from an input pen-gesture and the classification features of 15 pen-gestures types defined in the gesture model. The classification feature is using the insensitive stroke information. i.e., the positional relation between two strokes. the crossing number, the direction transition, the direction vector, the number of direction code. and the distance ratio between starting and ending point in each stroke. In the experiment, we acquired a high recognition rate and a fart speed.

An Emotional Gesture-based Dialogue Management System using Behavior Network (행동 네트워크를 이용한 감정형 제스처 기반 대화 관리 시스템)

  • Yoon, Jong-Won;Lim, Sung-Soo;Cho, Sung-Bae
    • Journal of KIISE:Software and Applications
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    • v.37 no.10
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    • pp.779-787
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    • 2010
  • Since robots have been used widely recently, research about human-robot communication is in process actively. Typically, natural language processing or gesture generation have been applied to human-robot interaction. However, existing methods for communication among robot and human have their limits in performing only static communication, thus the method for more natural and realistic interaction is required. In this paper, an emotional gesture based dialogue management system is proposed for sophisticated human-robot communication. The proposed system performs communication by using the Bayesian networks and pattern matching, and generates emotional gestures of robots in real-time while the user communicates with the robot. Through emotional gestures robot can communicate the user more efficiently also realistically. We used behavior networks as the gesture generation method to deal with dialogue situations which change dynamically. Finally, we designed a usability test to confirm the usefulness of the proposed system by comparing with the existing dialogue system.