• The KIPS Transactions:PartD
• /
• v.14D no.3 s.113
• /
• pp.311-318
• /
• 2007

A wearable computer has appeared as the next generation computer with the development of embedded system technique in our country, although it has not been applicable well since the hardware and software capabilities are limited for multimedia service. We have implemented a MPEG-4 video player to provide with such multimedia application service using the embedded systems. This paper illustrates the development of MPEG-4 video player operating on the wearable computer named WPS(Wearable Personal Station), the wristwatch PC developed at ETRI.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.12B
• /
• pp.831-837
• /
• 2005

Personal general purpose computer(PC) has been evolved from desktop to portable mobile device such as tablet PC and PDA. Technology innovation on semiconductor have made it possible to package a reasonably Powerful Processor and memory subsystem with advanced input/output devices. At last these subsystems are miniaturized into wearable system. Wearable computer has recently gained attention as the post PC in the ubiquitous environment. Wearable computing becomes more and more feasible and receives growing attention throughout industry and the consumer marketplaces. This paper proposed and developed WPS that has multimedia features and network features as a wearable embedded platform. We explain the form, overall architecture, functions and user applications of this WPS. This paper also discusses the form of next generation computer platform with intuitive user interfaces and well designed applications in the future.

• The KIPS Transactions:PartB
• /
• v.13B no.5 s.108
• /
• pp.561-568
• /
• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2006.06a
• /
• pp.57-62
• /
• 2006

휴대용 단말기의 소형화 및 지능화와 더불어 차세대 PC 기반의 유비쿼터스 컴퓨팅에 대한 관심이 높아짐에 따라 최근에는 펜이나 음성 입력 멀티미디어 등 여러 가지 대화 모드를 구비한 멀티 모달 상호작용 (Multi-Modal Interaction MMI)에 대한 연구가 활발히 진행되고 있다. 따라서, 본 논문에서는 잡음 환경에서의 명확한 의사 전달 및 휴대용 단말기에서의 음성-제스처 통합 인식을 위한 인터페이스의 연구를 목적으로 Voice-XML과 Wearable Personal Station(WPS) 기반의 음성 및 내장형 수화 인식기를 통합한 멀티 모달 명령어 인식 시스템 (Multi-Modal Instruction Recognition System : MMIRS)을 제안하고 구현한다. 제안되어진 MMIRS는 한국 표준 수화 (The Korean Standard Sign Language : KSSL)에 상응하는 문장 및 단어 단위의 명령어 인식 모델에 대하여 음성뿐만 아니라 화자의 수화제스처 명령어를 함께 인식하고 사용함에 따라 잡음 환경에서도 규정된 명령어 모델에 대한 인식 성능의 향상을 기대할 수 있다. MMIRS의 인식 성능을 평가하기 위하여, 15인의 피험자가 62개의 문장형 인식 모델과 104개의 단어인식 모델에 대하여 음성과 수화 제스처를 연속적으로 표현하고, 이를 인식함에 있어 개별 명령어 인식기 및 MMIRS의 평균 인식율을 비교하고 분석하였으며 MMIRS는 문장형 명령어 인식모델에 대하여 잡음환경에서는 93.45%, 비잡음환경에서는 95.26%의 평균 인식율을 나타내었다.