Efficient recognition and 6D pose tracking of markerless objects with RGB-D and motion sensors on mobile devices

Sheng Chu Huang, Wei Lun Huang, Yi Cheng Lu, Ming Han Tsai, I-Chen Lin, Yo Chung Lau, Hsu Hang Liu

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

This paper presents a system that can efficiently detect objects and estimate their 6D postures with RGB-D and motion sensor data on a mobile device. We apply a template-based method to detect the pose of an object, in which the matching process is accelerated through dimension reduction of the vectorized template matrix. After getting the initial pose, the proposed system then tracks the detected objects by a modified bidirectional iterative closest point algorithm. Furthermore, our system checks information from the inertial measurement unit on a mobile device to alleviate intensive computation for ease of interactive applications.

Conference

Conference14th International Conference on Computer Graphics Theory and Applications, GRAPP 2019 - Part of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019
Country/TerritoryCzech Republic
CityPrague
Period25/02/1927/02/19

Keywords

  • Markerless Tracking
  • Object Recognition
  • Pose Estimation
  • Sensors on Mobile Devices

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