Journal of the Korea Computer Graphics Society (한국컴퓨터그래픽스학회논문지)

Korea Computer Graphics Society (한국컴퓨터그래픽스학회)
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Motion correction captured by Kinect based on synchronized motion database

동기화된 동작 데이터베이스를 활용한 Kinect 포착 동작의 보정 기술

  • 박상일 (세종대학교 소프트웨어학과)
  • Received : 2017.04.19
  • Accepted : 2017.05.30
  • Published : 2017.06.01
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Abstract

In this paper, we present a method for data-driven correction of the noisy motion data captured from a low-end RGB-D camera such as the Kinect device. For this purpose, our key idea is to construct a synchronized motion database captured with Kinect and additional specialized motion capture device simultaneously, so that the database contains a set of erroneous poses from Kinect and their corresponding correct poses from the mocap device together. In runtime, given motion captured data from Kinect, we search the similar K candidate Kinect poses from the database, and synthesize a new motion only by using their corresponding poses from the mocap device. We present how to build such motion database effectively, and provide a method for querying and searching a desired motion from the database. We also adapt the laze learning framework to synthesize the corrected poses from the querying results.

본 논문은 Kinect와 같은 저가형 동작 포착 기기로부터 획득한 부정확한 동작데이터를 보정하여 올바른 동작을 생성하는 기술을 제안한다. 미리 정의된 동기화된 동작 데이터베이스를 활용하여 보정하는 것을 핵심아이디어로, 동기화된 데이터베이스란 Kinect와 함께 전문동작 포착 장비로 다양한 동작을 동시에 포착하여 시간축 상에서 동기화시켜 구성한 것을 의미한다. 구축된 동기화된 데이터베이스와 함께 오류가 있는 Kinect 동작 포착 데이터를 입력으로 받으면, 데이터베이스 검색을 통해 비슷한 자세군을 얻고 이로부터 올바른 자세를 통계학적으로 예측하는 지연학습방식의 보정방법을 제안한다. 본 방법의 유효성을 검증하기 위해 다양한 동작들에 대해 자세 보정을 실시하여 보정이 이뤄지는 것을 보였다.

Keywords

Acknowledgement

Supported by : 정보통신기술진흥센터

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