KIISE Transactions on Computing Practices (정보과학회 컴퓨팅의 실제 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Conceptual Group Activity Recognition Method in the Classroom Environment

강의실 환경에서의 집단 개념동작 인식 기법

  • 최정인 (이화여자대학교 컴퓨터공학과) ;
  • 용환승 (이화여자대학교 컴퓨터공학과)
  • Received : 2014.11.14
  • Accepted : 2015.02.14
  • Published : 2015.05.15
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Abstract

As smart phones with built-in sensors are developed, research on recognition using wearable devices is increasing. Existing papers are mostly limited on research to personal activity recognition. In this paper, we propose a method to recognize conceptual group activity. Before doing recognition, we generate new data based on the analysis of the conceptual group activity in a classroom. The study focuses on three activities in the classroom environment: Taking Lesson, Doing Presentation and Discussing. With the proposed algorithm, the recognition rate is over 96%. Using this method in real time will make it easy to automatically analyze the activity and the purpose of the classrooms. Moreover, it can increase the utilization of the classroom through the data analysis. Further research will focus on group activity recognition in other environments and the design of an group activity recognition system.

최근 다양한 센서를 내장한 스마트폰의 발달로 인해 웨어러블 기기를 사용한 동작 인식 연구가 늘어나는 추세이다. 기존의 동작 인식 연구는 사용자 개인의 동작 인식에만 국한되어 있다. 따라서 본 논문에서는 인간의 집단 개념동작을 인식하는 기법을 제안한다. 인식에 앞서 장소 별 집단 동작의 특징을 분석하여 데이터를 생성한다. 강의실 환경에서의 집단 개념동작을 중점적으로 수업하기, 발표하기, 회의하기로 세 가지 동작을 연구한다. 본 연구에서 제안한 알고리즘을 적용하여 96% 이상의 높은 인식률을 도출하였다. 실시간으로 활용한다면 자동적으로 강의실의 사용률 및 사용 목적을 쉽게 분석할 수 있다. 나아가 분석된 데이터를 통해 장소 활용도를 높일 수 있다. 향후 다른 장소에 대한 집단 동작 인식을 연구하여 집단 동작 인식 시스템을 개발할 것이다.

Keywords

Acknowledgement

Supported by : 한국연구재단

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