Image-based three-dimensional (3D) reconstruction is a process of extracting 3D information from an object or entire scene while using low-cost vision sensors. A structure-from-motion coupled with multi-view stereo (SFM-MVS) pipeline is a widely used technique that allows 3D reconstruction from a collection of unordered images. The SFM-MVS pipeline typically comprises different processing steps, including feature extraction and feature matching, which provide the basis for automatic 3D reconstruction. However, surfaces with poor visual texture (repetitive, monotone, etc.) challenge the feature extraction and matching stage and affect the quality of reconstruction. The projection of image patterns while using a video projector during the image acquisition process is a well-known technique that has been shown to be successful for such surfaces. In this study, we evaluate the performance of different feature extraction methods on texture-less surfaces with the application of synthetically generated noise patterns (images). Seven state-of-the-art feature extraction methods (HARRIS, Shi-Tomasi, MSER, SIFT, SURF, KAZE, and BRISK) are evaluated on problematic surfaces in two experimental phases. In the first phase, the 3D reconstruction of real and virtual planar surfaces evaluates image patterns while using all feature extraction methods, where the patterns with uniform histograms have the most suitable morphological features. The best performing pattern from Phase One is used in Phase Two experiments in order to recreate a polygonal model of a 3D printed object using all of the feature extraction methods. The KAZE algorithm achieved the lowest standard deviation and mean distance values of 0.0635 mm and −0.00921 mm, respectively.

Floating holograms using holographic optical element screens differ from existing systems because they can float 2D images in the air and provide a sense of depth. Until now, the verification of such displays has been conducted only on the system implementation, and only the diffraction efficiency and angle of view of the hologram have been verified. Although such displays can be directly observed with the human eye, the eye’s control ability has not been quantitatively verified. In this study, we verified that the focus of the observer coincided with the appropriate depth value determined with experiments. This was achieved by measuring the amount of control reaction from the perspective of the observer on the image of the floating hologram using a holographic optical element (HOE). An autorefractor was used, and we confirmed that an image with a sense of depth can be observed from the interaction of the observer’s focus and convergence on the 2D floating image using a HOE. Thus, the realization of content with a sense of depth of 2D projected images using a HOE in terms of human factors was quantitatively verified.

Vergence and accommodation responses of human vision are very important factors when a 3D image is observed, and a vergence-accommodation conflict (VAC) causes perceptual distortion, visual discomfort, and fatigue for an observer. Theoretically, a hologram is expected to provide a 3D image without such a conflict. In this article, natural focusing was verified by human accommodation response (A-R) measurement during on-axis analog reflection Denisyuk hologram observation. The A-R of a group of participants were measured for a real marker and its Denisyuk hologram at various visualization distances using an Nvision K5001 autorefractor. The experimental results statistically confirmed the equivalence of the responses to the Denisyuk hologram and its real counterpart, as well as the absence of a VAC.