Abstract
Abstract. Due to the development of action cameras, the use of video technology for collecting geo-spatial data becomes an important trend. The objective of this study is to compare the image-mode and video-mode of multiple action cameras for 3D point clouds generation. Frame images are acquired from discrete camera stations while videos are taken from continuous trajectories. The proposed method includes five major parts: (1) camera calibration, (2) video conversion and alignment, (3) orientation modelling, (4) dense matching, and (5) evaluation. As the action cameras usually have large FOV in wide viewing mode, camera calibration plays an important role to calibrate the effect of lens distortion before image matching. Once the camera has been calibrated, the author use these action cameras to take video in an indoor environment. The videos are further converted into multiple frame images based on the frame rates. In order to overcome the time synchronous issues in between videos from different viewpoints, an additional timer APP is used to determine the time shift factor between cameras in time alignment. A structure form motion (SfM) technique is utilized to obtain the image orientations. Then, semi-global matching (SGM) algorithm is adopted to obtain dense 3D point clouds. The preliminary results indicated that the 3D points from 4K video are similar to 12MP images, but the data acquisition performance of 4K video is more efficient than 12MP digital images.
Highlights
1.1 MotivationThree-dimensional geospatial information of indoor environment can be generated from cameras and laser scanners
The spatial resolution of a digital still camera is higher than a digital video, the sampling rate of a digital video is better than a digital still camera
Due to the light weight, low cost and high spatial resolution of video mode, the usage of action cameras are extended to unmanned aerial vehicle (UAV), mobile mapping system (MMS), and other photogrammetric purposes
Summary
Three-dimensional geospatial information of indoor environment can be generated from cameras and laser scanners. Laser scanners obtain 3D points directly while camera indirectly obtains 3D points via stereo image matching. Digital still cameras and digital videos are two possible ways to collect digital images for image matching. A lightweight action camera such as GoPro Hero 4 Black Edition is able to collect digital still images up to 12Mp (4000 x 3000) resolution and video up to 8.3MP (3840 x 2160) resolution at 30 frames per second. Action camera is able to acquire both video and image (5 seconds per frame) simultaneously. Due to the light weight, low cost and high spatial resolution of video mode, the usage of action cameras are extended to unmanned aerial vehicle (UAV), mobile mapping system (MMS), and other photogrammetric purposes
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