Search Results (138)

This paper presents a prototype for an assistive navigation system that integrates three-dimensional audio spatialization with computer vision to improve the mobility of visually impaired individuals. The system uses stereoscopic depth perception and real-time point cloud reconstruction alongside a modified YOLO convolutional neural network for object detection and auralization techniques with head-related impulse response functions. Twenty participants (ten who were visually impaired and ten who were blindfolded) navigated controlled obstacle scenarios while wearing a chest-mounted camera and specialized headphones. The prototype achieved 95.00% precision in object classification across eleven obstacle categories and a 33.19% recall, indicating conservative detection behavior. The processing efficiency was 0.042489 s per image, which exceeds real-time requirements. User evaluation revealed an average collision rate of 0.5 per scenario and a mean completion time of 48 s. Statistical analysis showed no significant difference in collision rates between participant groups ($p=0.172$), though visually impaired participants demonstrated faster completion times ($p=0.003$). Integrating segmented, convolution-based audio processing with stereoscopic depth estimation enabled users to perceive obstacle locations through spatial sound cues, establishing a foundation for advancing assistive navigation technologies without extensive training. Full article

Virtual reality (VR) interfaces increasingly rely on interaction within peripersonal space. However, the conditions under which interaction performance in virtual environments can approximate those of comparable real-world tasks remain underexplored, particularly for hierarchical menus requiring precise sequential input. This study investigated how the presence or absence of tactile feedback influences movement time and selection accuracy during hierarchical menu interaction in peripersonal space across different task difficulty levels. Twelve participants performed a three-level hierarchical selection task on a 4 × 3 menu in two controlled experiments with a stereoscopic 3D TV. Two interaction conditions were tested: a surface-based condition, with the menu attached to the physical screen, and a mid-air condition, with the menu positioned 35 cm and 45 cm in front of participants. Selections were confirmed using a handheld remote. Results showed no statistically significant difference in movement time and selection accuracy between the virtual and real environments when screen-surface targets provided tactile feedback, but performance declined for mid-air targets without tactile references, particularly under higher task difficulty levels. These findings suggest that tactile feedback, coordinated visual target placement, and users’ familiarity with touchscreen-like interaction jointly act as key factors for designing effective, immersive, and user-friendly VR menu systems in peripersonal space. Full article

Micro-scale counter-rotating wind turbines (CRWTs) offer enhanced potential for wake energy recovery. This study proposes an integrated cascade–coupling design framework for high-solidity CRWTs, in which rear rotor geometry and rotor coupling are co-designed based on stereoscopic particle image velocimetry measurements of the front rotor wake. Experiments are conducted at a tip-speed ratio of $\lambda =1.0$, solidity $\sigma =1.25$, spacing ratios of $d=0.6R_T$, $1.0R_T$, and $3.0R_T$, and a tip radius of $R_T=70$ mm. At the physical limit spacing of $d=0.6R_T$, the integrated design increases the system power coefficient by 24.1% while limiting front rotor power reduction to 17.2%, compared to a 10.3% system gain and 34.5% front rotor suppression for the baseline mirrored configuration. Wake measurements confirm near-complete absorption of rotational kinetic energy from the front rotor wake without exacerbating upstream interference. These results demonstrate that cascade-based energy extraction and coupling-based interference mitigation can operate synergistically, enabling compact, high-performance micro-scale CRWTs suitable for space-constrained and urban energy applications. Full article

The presence of microplastics (<5 mm) has become a major threat to marine ecosystems and the organisms inhabiting them. This issue affects a wide range of animals, including commercially important marine fish, whose ingestion of microplastics can cause mechanical and metabolic damage. This study aimed to characterize the main types of microplastic-like particles ingested by Centropomus viridis, Cynoscion othonopterus, Pomadasys macracanthus, Diapterus peruvianus, Lutjanus colorado, and Scomberomorus sierra, important commercial fish species in northwestern Mexico. Four sampling events were conducted over an annual cycle (November to August) in the lagoon and insular systems of Navachiste and Ohuira, Sinaloa, Mexico (RAMSAR sites 1826 and 2025). A total of 556 individuals were captured, and their stomach contents were analyzed using stereoscopic microscopy. Systematic sediment sampling was also performed at each capture site (El Coloradito, El Caracol, El Huitussi, El Aparecido, El Cerro Cabezón, Topolobampo, El Cerro Partido, and El Tortugo) by examining the upper 30 cm of sediment to ensure representativeness of the particle inventory. Four of the six analyzed species (C. viridis, C. othonopterus, P. macracanthus, and D. peruvianus) contained microplastic-like particles (MP-p), totaling 163 items, with an average ingestion rate of 0.29 items individual⁻¹. The omnivorous species D. peruvianus showed the highest ingestion (0.52 items individual⁻¹; 0.0029 items g⁻¹ wet weight). Five categories of MP-p were distinguished based on morphology and fluorescence; however, their polymeric identity cannot be confirmed without spectroscopic analyses. Sediment results showed that most microplastic-like fragments occurred at site 2025 during autumn, spring, and summer, while levels at site 1826 did not differ significantly. This study provides the first evidence of microplastic contamination in these fish species and in this region of northwestern Mexico. Full article

The identification of lithology and fluids in reservoirs is the key to the quantitative characterization of gas reservoirs. However, the Ma5₄¹ Member of the Majiagou Formation in the Ordos Basin is characterized by strong reservoir heterogeneity, variable lithologic components and complex gas–water relationships. This leads to severe overlapping of conventional logging responses, posing significant challenges to detailed reservoir evaluation. Taking the Ma5₄¹ Member in the central Shaanbei Slope of the Ordos Basin as the research object, this study adopts the logging curve superposition and reconstruction method to quantitatively identify reservoir lithology and fluid properties, and establishes a set of identification standards for lithology-fluid logging curve superposition and reconstruction. The results show that the lithology identification plate constructed by introducing new parameters eliminates dimensional differences and effectively highlights the response characteristics of different lithologies. It can rapidly and effectively identify limestone, limy dolomite, dolomite, argillaceous dolomite, and mudstone with an identification accuracy exceeding 90% and an average accuracy of over 92%. In terms of fluid identification, the constructed ΔΦ₃–ΔΦ₄–ΔΦ₅ 3D plate successfully achieved the stereoscopic differentiation of gas layers, gas-bearing water layers, water layers, and dry layers. The gas layer identification accuracy reached 93.9%, which is significantly superior to the traditional 2D crossplot method. Applying this model to the plane prediction of lithology in the Ma5₄¹ Member of the study area, it was found that the lithology distribution features “pure in the east and mixed in the west.” The central-eastern and southeastern parts of the study area mainly develop high-quality dolomite and limy dolomite reservoirs, making them favorable areas for natural gas exploration. This study provides effective technical support for the quantitative identification of lithology and fluids in non-cored well sections and improves regional exploration and development efficiency. Full article

We present a stereoscopic analysis of coronal streamer deflection induced by a CME-driven shock, utilizing multi-viewpoint coronagraph observations from STEREO-Ahead, STEREO-Behind, and SOHO. Driven by the continuous impact of the shock, the streamer deflection propagates outward, exhibiting distinct morphological variations across the three different lines of sight. Our analysis reveals that speeds derived directly from two-dimensional (2D) images differ significantly from those obtained via three-dimensional (3D) reconstruction. Specifically, the 2D projected speeds measured from STEREO-Ahead, STEREO-Behind, and SOHO are 445, 476, and 336 km s⁻¹, respectively. Furthermore, while 2D measurements suggest a constant propagation speed, the 3D reconstruction reveals a pronounced deceleration of approximately −36 m s⁻². Significant discrepancies are also noted in the deflection amplitude between the 2D and 3D results. Since the propagating streamer deflection effectively traces the shock’s movement, we propose that measuring the deflection speed offers a robust alternative for deriving actual shock velocities in the outer corona, where direct white-light detection remains challenging. Full article

This paper presents an immersive teleoperation framework for service robots that combines real-time 3D human pose estimation with a Virtual Reality (VR) interface to support intuitive, natural robot control. The operator is tracked using MediaPipe for 2D landmark detection and an Intel RealSense D455 RGB-D (Red-Green-Blue plus Depth) camera for depth acquisition, enabling 3D reconstruction of key joints. Joint angles are computed using efficient vector operations and mapped to the kinematic constraints of an anthropomorphic arm on the CHARMIE service robot. A VR-based telepresence interface provides stereoscopic video and head-motion-based view control to improve situational awareness during manipulation tasks. Experiments in real-world object grasping demonstrate reliable arm teleoperation and effective telepresence; however, vision-only estimation remains limited for axial rotations (e.g., elbow and wrist yaw), particularly under occlusions and unfavorable viewpoints. The proposed system provides a practical pathway toward low-cost, sensor-driven, immersive human–robot interaction for service robotics in dynamic environments. Full article

Three-dimensional (3D) printing enables accurate implant pre-shaping in orbital reconstruction but is costly and time-consuming. Naked-eye stereoscopic displays (NEDs) enable virtual implant modeling without fabrication. This study aimed to compare the reproducibility and accuracy of NED-based virtual reality (VR) pre-shaping with conventional 3D-printed models. Two surgeons pre-shaped implants for 11 unilateral orbital floor fractures using both 3D-printed and NED-based VR models with identical computed tomography data. The depth, area, and axis dimensions were measured, and reproducibility and agreement were assessed using intraclass correlation coefficients (ICCs), Bland–Altman analysis, and shape similarity metrics—Hausdorff distance (HD) and root mean square error (RMSE). Intra-rater ICCs were ≥0.80 for all parameters except depth in the VR model. The HD and RMSE reveal no significant differences between 3D (2.64 ± 0.85 mm; 1.02 ± 0.42 mm) and VR (3.14 ± 1.18 mm; 1.24 ± 0.53 mm). Inter-rater ICCs were ≥0.80 for the area and axes in both modalities, while depth remained low. Between modalities, no significant differences were found; HD and RMSE were 2.95 ± 0.94 mm and 1.28 ± 0.49 mm. The NED-based VR pre-shaping achieved reproducibility and dimensional agreement comparable to 3D printing, suggesting a feasible cost- and time-efficient alternative for orbital reconstruction. These preliminary findings suggest that NED-based preshaping may be feasible; however, larger studies are required to confirm whether VR can achieve performance comparable to 3D-printed models. Full article

This study presents an experimental methodology for characterizing the crack-tip region using high-resolution Digital Image Correlation (DIC). The approach utilizes a stereoscopic microscope setup combined with 3D-DIC analysis to enable precise measurements within the small-scale region surrounding the crack tip. Two nonlinear parameters are evaluated: the plastic component of the crack-tip opening displacement (CTOD_p) and the cyclic plastic zone size. The investigation was conducted on disk-shaped compact tension specimens made of AISI 1020 steel under constant-ΔK fatigue testing. The results demonstrate a strong correlation between these nonlinear parameters and fatigue crack propagation, which was maintained stable, validating the proposed methodology. Furthermore, the relevance of crack-tip plasticity in fatigue crack propagation is verified under the tested conditions, highlighting its utility for fatigue life assessment under complex loading scenarios. Full article

The increasing use of immersive 3-D technologies in education raises critical questions about their cognitive impact on learners. This systematic review evaluates how electroencephalography (EEG) and eye-tracking have been used to objectively measure cognitive load in 3-D learning environments. We conducted a comprehensive literature search (2009–2025) across PubMed, Scopus, Web of Science, PsycInfo, and ERIC, identifying 51 studies that used EEG or eye-tracking in experimental contexts involving stereoscopic or head-mounted 3-D technologies. Our findings suggest that 3-D environments may enhance learning and engagement, particularly in spatial tasks, while affecting cognitive load in complex, task-dependent ways. Studies reported mixed patterns across psychophysiological measures, including spectral features (e.g., frontal theta, parietal alpha), workload indices (e.g., theta/alpha ratio), and gaze-based metrics (e.g., fixation duration, pupil dilation): some studies observed increased load, while others reported reductions or no difference. These discrepancies reflect methodological heterogeneity and underscore the value of time-sensitive assessments. While a moderate cognitive load supports learning, an excessive load may impair performance, and overload thresholds can vary across individuals. EEG and eye-tracking offer scalable methods for monitoring cognitive effort dynamically. Overall, 3-D and XR technologies hold promise but must be aligned with task demands and learner profiles and guided by real-time indicators of cognitive load in immersive environments. Full article

The Surface Extraction by TIN-based Search-space Minimization (SETSM) algorithm provides automatic generation of stereo-photogrammetric Digital Surface Models (DSMs) from single stereopairs of stereoscopic images (i.e., stereopairs), eliminating the need for terrain-dependent parameters. SETSM has been extensively validated through the ArcticDEM and Reference Elevation Models for Antarctica (REMA) DSM mapping projects. To enhance DSM coverage, quality, and accuracy by addressing stereopair occlusions, we expand the capabilities of the SETSM algorithm from single stereopair to multiple-pair matching. Building on SETSM’s essential components, we present a SETSM multiple-pair matching procedure (SETSM MMP) that modifies 3D voxel construction, similarity measurement, and blunder detection, among other components. A novel Three-Dimensional Kernel-based Weighted Height Estimation (3D KWHE) algorithm specialized for SETSM accurately determines optimal heights and reduces surface noise. Additionally, an adaptive pixel-to-pixel matching strategy mitigates the effect of differences in ground sample distance (GSD) between images. Validation using space-borne Worldview-2 and air-borne DMC multiple images over urban landscapes, compared to USGS lidar DSM, confirms improved height accuracy and matching success rates. The results from the DMC air-borne images demonstrate efficient elimination of occlusions. SETSM MMP enables high-quality DSM generation in urban environments while retaining the original, single-stereopair SETSM’s high performance. Full article

This study proposes an image processing framework based on bionic principles to optimize 3D visual perception in virtual reality (VR) systems. By simulating the physiological mechanisms of the human visual system, the framework significantly enhances depth perception and visual fidelity in VR content. The research focuses on three core algorithms: Gabor texture feature extraction algorithm based on directional selectivity of neurons in the V1 region of the visual cortex, which enhances edge detection capability through fourth-order Gaussian kernel; improved Retinex model based on adaptive mechanism of retinal illumination, achieving brightness balance under complex illumination through horizontal–vertical dual-channel decomposition; the RGB adaptive adjustment algorithm, based on the three color response characteristics of cone cells, integrates color temperature compensation with depth cue optimization, enhances color naturalness and stereoscopic depth. Build a modular processing system on the Unity platform, integrate the above algorithms to form a collaborative optimization process, and ensure per-frame processing time meets VR real-time constraints. The experiment uses RMSE, AbsRel, and SSIM metrics, combined with subjective evaluation to verify the effectiveness of the algorithm. The results show that compared with traditional methods (SSAO, SSR, SH), our algorithm demonstrates significant advantages in simple scenes and marginal superiority in composite metrics for complex scenes. Collaborative processing of three algorithms can significantly improve depth map noise and enhance the user’s subjective experience. The research results provide a solution that combines biological rationality and engineering practicality for visual optimization in fields such as implantable metaverse, VR healthcare, and education. Full article

Background and Objectives: Depth perception of the human visual system in three-dimensional (3D) space plays an important role in human–computer interaction and artificial intelligence (AI) areas. It mainly employs binocular disparity and motion parallax cues. This study aims to systemically summarize the related studies about depth perception specified by these two cues. Materials and Methods: We conducted a literature investigation on related studies and summarized them from aspects like motivations, research trends, mechanisms, and interaction models of depth perception specified by these two cues. Results: Development trends show that depth perception research has gradually evolved from early studies based on a single cue to quantitative studies based on the interaction between these two cues. Mechanisms of these two cues reveal that depth perception specified by the binocular disparity cue is mainly influenced by factors like spatial variation in disparity, viewing distance, the position of visual field (or retinal image) used, and interaction with other cues; whereas that specified by the motion parallax cue is affected by head movement and retinal image motion, interaction with other cues, and the observer’s age. By integrating these two cues, several types of models for depth perception are summarized: the weak fusion (WF) model, the modified weak fusion (MWF) model, the strong fusion (SF) model, and the intrinsic constraint (IC) model. The merits and limitations of each model are analyzed and compared. Conclusions: Based on this review, a clear picture of the study on depth perception specified by binocular disparity and motion parallax cues can be seen. Open research challenges and future directions are presented. In the future, it is necessary to explore methods for easier manipulating of depth cue signals in stereoscopic images and adopting deep learning-related methods to construct models and predict depths, to meet the increasing demand of human–computer interaction in complex 3D scenarios. Full article

In the context of sea levels rising, monitoring spatial and temporal topographic changes along coastal dunes is crucial to understand their dynamics since they represent natural barriers against coastal flooding and large sources of sediment that can mitigate coastal erosion. Different technologies are currently used to monitor coastal dune topographic changes (GNSS, UAV, airborne LiDAR, etc.). Satellites recently emerged as a new source of topographic data by providing high-resolution images with a rather short revisit time at the global scale. Stereoscopic or tri-stereoscopic acquisition of some of these images enables the creation of 3D models using stereophotogrammetry methods. Here, the Ames Stereo Pipeline was used to produce digital elevation models (DEMs) from tri-stereo panchromatic and high-resolution Pleiades images along three 19 km long stretches of coastal dunes in SW France. The vertical errors of the Pleiades-derived DEMs were assessed by comparing them with DEMs produced from airborne LiDAR data collected a few months apart from the Pleiades images in 2017 and 2021 at the same three study sites. Results showed that the Pleiades-derived DEMs could reproduce the overall dune topography well, with averaged root mean square errors that ranged from 0.5 to 1.1 m for the six sets of tri-stereo images. The differences between DEMs also showed that Pleiades images can be used to monitor multi-annual coastal dune morphological changes. Strong erosion and accretion patterns over spatial scales ranging from hundreds of meters (e.g., blowouts) to tens of kilometers (e.g., dune retreat) were captured well, and allowed to quantify changes with reasonable errors (30%). Furthermore, relatively small averaged root mean square errors (0.63 m) can be obtained with a limited number of field-collected elevation points (five ground control points) to perform a simple vertical correction on the generated Pleiades DEMs. Among different potential sources of errors, shadow areas due to the steepness of the dune stoss slope and crest, along with planimetric errors that can also occur due to the steepness of the terrain, remain the major causes of errors still limiting accurate enough volumetric change assessment. However, ongoing improvements on the stereo matching algorithms and spatial resolution of the satellite sensors (e.g., Pleiades Neo) highlight the growing potential of Pleiades images as a cost-effective alternative to other mapping techniques of coastal dune topography. Full article

Spatio-temporal measurements of turbulent free surface flows remain challenging with in situ point methods. This study explores the application of an inexpensive depth-sensing RGB-D camera, the Intel^® RealSense™ D455, to capture detailed water surface measurements of a highly turbulent, self-aerated flow in the case of a stepped spillway. Ambient lighting conditions and various sensor settings, including configurations and parameters affecting data capture and quality, were assessed. A free surface profile was extracted from the 3D measurements and compared against phase detection conductivity probe (PDCP) and ultrasonic sensor (USS) measurements. Measurements in the non-aerated region were influenced by water transparency and a lack of detectable surface features, with flow depths consistently smaller than USS measurements (up to 32.5% less). Measurements in the clear water region also resulted in a “no data” region with holes in the depth map due to shiny reflections. In the aerated flow region, the camera effectively detected the dynamic water surface, with mean surface profiles close to characteristic depths measured with PDCP and within one standard deviation of the mean USS flow depths. The flow depths were within 10% of the USS depths and corresponded to depths with 80–90% air concentration levels obtained with the PDCP. Additionally, the depth camera successfully captured temporal fluctuations, allowing for the calculation of time-averaged entrapped air concentration profiles and dimensionless interface frequency distributions. This facilitated a direct comparison with PDCP and USS sensors, demonstrating that this camera sensor is a practical and cost-effective option for detecting free surfaces of high velocity, aerated, and dynamic flows in a stepped chute. Full article