AUTOMATED REGISTRATION OF SfM-MVS MULTITEMPORAL DATASETS USING TERRESTRIAL AND OBLIQUE AERIAL IMAGES

Accurate alignment of 3D models is critical for valid change-detection analysis from multitemporal photogrammetric datasets. This paper assesses an automated registration strategy which uses the scale-invariant feature transform (SIFT) algorithm implemented in modern photogrammetric software. This registration solution, also known as "Time-SIFT", was tested at two study sites featuring vertical surfaces, including a sea cliff (similar to 500 m(2)) and a quarry face (similar to 50 000 m(2)). Tests demonstrated that the investigated registration strategy can achieve accurate alignments between multitemporal point clouds even when using multisource and multi-perspective data, captured across widely varying spatial and temporal scales and under a range of weather and illumination conditions. The combination of the Time-SIFT approach with an ICP algorithm produced moderate improvements in the alignment. Furthermore, the use of an innovative direct georeferencing technique, which used the tracking feature of a robotic total station, allowed for accurate georectification of 3D models.