POINT CLOUD DERIVED FROMVIDEO FRAMES: ACCURACY ASSESSMENT IN RELATION TO TERRESTRIAL LASER SCANNINGAND DIGITAL CAMERA DATA
Keywords: Dense image matching, 3D modelling, data integration, image sequence, HBIM, video frames selection
Abstract. The use of image sequences in the form of video frames recorded on data storage is very useful in especially when working with large and complex structures. Two cameras were used in this study: Sony NEX-5N (for the test object) and Sony NEX-VG10 E (for the historic building). In both cases, a Sony α f = 16 mm fixed focus wide-angle lens was used. Single frames with sufficient overlap were selected from the video sequence using an equation for automatic frame selection. In order to improve the quality of the generated point clouds, each video frame underwent histogram equalization and image sharpening. Point clouds were generated from the video frames using the SGM-like image matching algorithm. The accuracy assessment was based on two reference point clouds: the first from terrestrial laser scanning and the second generated based on images acquired using a high resolution camera, the NIKON D800. The performed research has shown, that highest accuracies are obtained for point clouds generated from video frames, for which a high pass filtration and histogram equalization had been performed. Studies have shown that to obtain a point cloud density comparable to TLS, an overlap between subsequent video frames must be 85 % or more. Based on the point cloud generated from video data, a parametric 3D model can be generated. This type of the 3D model can be used in HBIM construction.