Volume XLII-2/W8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W8, 187-194, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W8-187-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W8, 187-194, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W8-187-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Nov 2017

14 Nov 2017

3D RECONSTRUCTION WITH A COLLABORATIVE APPROACH BASED ON SMARTPHONES AND A CLOUD-BASED SERVER

E. Nocerino1, F. Poiesi2, A. Locher3, Y. T. Tefera2, F. Remondino1, P. Chippendale2, and L. Van Gool3 E. Nocerino et al.
  • 13D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy
  • 2Technologies of Vision (TeV) unit, Bruno Kessler Foundation (FBK), Trento, Italy
  • 3Computer Vision Lab, ETH Zurich, Switzerland

Keywords: smartphone, 3D reconstruction, low-cost, collaborative, SfM, photogrammetry, dense image matching

Abstract. The paper presents a collaborative image-based 3D reconstruction pipeline to perform image acquisition with a smartphone and geometric 3D reconstruction on a server during concurrent or disjoint acquisition sessions. Images are selected from the video feed of the smartphone’s camera based on their quality and novelty. The smartphone’s app provides on-the-fly reconstruction feedback to users co-involved in the acquisitions. The server is composed of an incremental SfM algorithm that processes the received images by seamlessly merging them into a single sparse point cloud using bundle adjustment. Dense image matching algorithm can be lunched to derive denser point clouds. The reconstruction details, experiments and performance evaluation are presented and discussed.