Various touch-based interaction techniques have been developed to make interactions on mobile
devices more effective, efficient, and intuitive. Finger orientation, especially, has attracted a
lot of attentions since it intuitively brings three additional degrees of freedom (DOF) compared
with two-dimensional (2D) touching points. The mapping of finger orientation can be classified as
being either absolute or relative, suitable for different interaction applications. However, only
absolute orientation has been explored in prior works. The relative angles can be calculated based
on two estimated absolute orientations, although, a higher accuracy is expected by predicting
relative rotation from input images directly. Consequently, in this paper, we propose to estimate
complete 3D relative finger angles based on two fingerprint images, which incorporate more
information with a higher image resolution than capacitive images. For algorithm training and
evaluation, we constructed a dataset consisting of fingerprint images and their corresponding
ground truth 3D relative finger rotation angles. Experimental results on this dataset revealed
that our method outperforms previous approaches with absolute finger angle models. Further,
extensive experiments were conducted to explore the impact of image resolutions, finger types, and
rotation ranges on performance. A user study was also conducted to examine the efficiency and
precision using 3D relative finger orientation in 3D object rotation task.