• Title, Summary, Keyword: recognition

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Bayesian Method Recognition Rates Improvement using HMM Vocabulary Recognition Model Optimization (HMM 어휘 인식 모델 최적화를 이용한 베이시안 기법 인식률 향상)

  • Oh, Sang Yeon
    • Journal of Digital Convergence
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    • v.12 no.7
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    • pp.273-278
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    • 2014
  • In vocabulary recognition using HMM(Hidden Markov Model) by model for the observation of a discrete probability distribution indicates the advantages of low computational complexity, but relatively low recognition rate. Improve them with a HMM model is proposed for the optimization of the Bayesian methods. In this paper is posterior distribution and prior distribution in recognition Gaussian mixtures model provides a model to optimize of the Bayesian methods vocabulary recognition. The result of applying the proposed method, the recognition rate of 97.9% in vocabulary recognition, respectively.

Improvement of Gesture Recognition using 2-stage HMM (2단계 히든마코프 모델을 이용한 제스쳐의 성능향상 연구)

  • Jung, Hwon-Jae;Park, Hyeonjun;Kim, Donghan
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.11
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    • pp.1034-1037
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    • 2015
  • In recent years in the field of robotics, various methods have been developed to create an intimate relationship between people and robots. These methods include speech, vision, and biometrics recognition as well as gesture-based interaction. These recognition technologies are used in various wearable devices, smartphones and other electric devices for convenience. Among these technologies, gesture recognition is the most commonly used and appropriate technology for wearable devices. Gesture recognition can be classified as contact or noncontact gesture recognition. This paper proposes contact gesture recognition with IMU and EMG sensors by using the hidden Markov model (HMM) twice. Several simple behaviors make main gestures through the one-stage HMM. It is equal to the Hidden Markov model process, which is well known for pattern recognition. Additionally, the sequence of the main gestures, which comes from the one-stage HMM, creates some higher-order gestures through the two-stage HMM. In this way, more natural and intelligent gestures can be implemented through simple gestures. This advanced process can play a larger role in gesture recognition-based UX for many wearable and smart devices.

Behavior recognition system based fog cloud computing

  • Lee, Seok-Woo;Lee, Jong-Yong;Jung, Kye-Dong
    • International journal of advanced smart convergence
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    • v.6 no.3
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    • pp.29-37
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    • 2017
  • The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

A Study on Convergence Development Direction of Gesture Recognition Game (동작 인식 게임의 융합 발전 방향)

  • Lee, MyounJae
    • Journal of the Korea Convergence Society
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    • v.5 no.4
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    • pp.1-7
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    • 2014
  • Gesture recognition provides the ease and immediacy to users in the processing technique for recognizing the gesture. Because of these benefits, gesture recognition technology has been applied and fused in many areas, such as the military, health care, education. In particular, the gesture recognition in game field since it can provide users to play games similar to the actual gesture, it being fused with many areas such as medical, military, and education. This paper is to discuss the future convergence direction of motion recognition games based on this background. In this paper, it looks at technology status and the game of gesture recognition, describe the problem and improvement of gesture recognition game. This paper can help improving the competitiveness of domestic convergence on gesture recognition game.

The Vocabulary Recognition Optimize using Acoustic and Lexical Search (음향학적 및 언어적 탐색을 이용한 어휘 인식 최적화)

  • Ahn, Chan-Shik;Oh, Sang-Yeob
    • Journal of Korea Multimedia Society
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    • v.13 no.4
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    • pp.496-503
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    • 2010
  • Speech recognition system is developed of standalone, In case of a mobile terminal using that low recognition rate represent because of limitation of memory size and audio compression. This study suggest vocabulary recognition highest performance improvement system for separate acoustic search and lexical search. Acoustic search is carry out in mobile terminal, lexical search is carry out in server processing system. feature vector of speech signal extract using GMM a phoneme execution, recognition a phoneme list transmission server using Lexical Tree Search algorithm lexical search recognition execution. System performance as a result of represent vocabulary dependence recognition rate of 98.01%, vocabulary independence recognition rate of 97.71%, represent recognition speed of 1.58 second.

A Hand Gesture Recognition Method using Inertial Sensor for Rapid Operation on Embedded Device

  • Lee, Sangyub;Lee, Jaekyu;Cho, Hyeonjoong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.757-770
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    • 2020
  • We propose a hand gesture recognition method that is compatible with a head-up display (HUD) including small processing resource. For fast link adaptation with HUD, it is necessary to rapidly process gesture recognition and send the minimum amount of driver hand gesture data from the wearable device. Therefore, we use a method that recognizes each hand gesture with an inertial measurement unit (IMU) sensor based on revised correlation matching. The method of gesture recognition is executed by calculating the correlation between every axis of the acquired data set. By classifying pre-defined gesture values and actions, the proposed method enables rapid recognition. Furthermore, we evaluate the performance of the algorithm, which can be implanted within wearable bands, requiring a minimal process load. The experimental results evaluated the feasibility and effectiveness of our decomposed correlation matching method. Furthermore, we tested the proposed algorithm to confirm the effectiveness of the system using pre-defined gestures of specific motions with a wearable platform device. The experimental results validated the feasibility and effectiveness of the proposed hand gesture recognition system. Despite being based on a very simple concept, the proposed algorithm showed good performance in recognition accuracy.

Feature Extraction Method for the Character Recognition of the Low Resolution Document

  • Kim, Dae-Hak;Cheong, Hyoung-Chul
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.3
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    • pp.525-533
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    • 2003
  • In this paper we introduce some existing preprocessing algorithm for character recognition and consider feature extraction method for the recognition of low resolution document. Image recognition of low resolution document including fax images can be frequently misclassified due to the blurring effect, slope effect, noise and so on. In order to overcome these difficulties in the character recognition we considered a mesh feature extraction and contour direction code feature. System for automatic character recognition were suggested.

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A Study on the Isolated word Recognition Using One-Stage DMS/DP for the Implementation of Voice Dialing System

  • Seong-Kwon Lee
    • Proceedings of the Acoustical Society of Korea Conference
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    • pp.1039-1045
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    • 1994
  • The speech recognition systems using VQ have usually the problem decreasing recognition rate, MSVQ assigning the dissimilar vectors to a segment. In this paper, applying One-stage DMS/DP algorithm to the recognition experiments, we can solve these problems to what degree. Recognition experiment is peformed for Korean DDD area names with DMS model of 20 sections and word unit template. We carried out the experiment in speaker dependent and speaker independent, and get a recognition rates of 97.7% and 81.7% respectively.

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A rule-based recognition system for korean spoken place names

  • Choi, Won-Kyu;Lee, Fi-Hyol;Akizuki, Kageo
    • 제어로봇시스템학회:학술대회논문집
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    • pp.431-436
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    • 1989
  • A rule-based recognition system for Korean spoken place names using anti-formants which is analyzed by ARMA model is presented. The recognition system is composed of three parts; the extraction, the recognition and the recognition support. As a result of experiment, the recognition rates of city place names was 90.9%.

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Implementation of Connected-Digit Recognition System Using Tree Structured Lexicon Model (트리 구조 어휘 사전을 이용한 연결 숫자음 인식 시스템의 구현)

  • Yun Young-Sun;Chae Yi-Geun
    • MALSORI
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    • no.50
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    • pp.123-137
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    • 2004
  • In this paper, we consider the implementation of connected digit recognition system using tree structured lexicon model. To implement efficiently the fixed or variable length digit recognition system, finite state network (FSN) is required. We merge the word network algorithm that implements the FSN with lexical tree search algorithm that is used for general speech recognition system for fast search and large vocabulary systems. To find the efficient modeling of digit recognition system, we investigate some performance changes when the lexical tree search is applied.

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