Search Results (252)

Background: Sensor-based systems and virtual reality (VR) technologies provide new opportunities for the objective, technology-driven assessment and training of visuomotor performance in applied contexts such as sport. Methods: This study examined the effects of an integrated visual training program combining stroboscopic stimulation, VR-based vergence exercises, and instrumented reaction-light tasks in adolescent handball players. Twenty-eight adolescent handball players (under-18 competitive level) completed two baseline assessments separated by six weeks, followed by a six-session training program (approximately 15 min per session) integrated into regular team practice. The intervention targeted visuomotor reaction speed, accommodative dynamics, and peripheral visual responsiveness using sensor-based and virtual reality–assisted stimuli. Results: Compared with both baseline measurements, the intervention produced selective improvements in accommodative facility (cycles per minute, cpm)—particularly near–far focusing speed—and in multiple reaction-time conditions (milliseconds, ms) involving manual and decision-based responses. Specific peripheral-field locations showed increased response scores, whereas binocular alignment, AC/A ratio, near phoria, and stereoscopic acuity remained unchanged. Conclusions: These findings indicate that technology-supported visual training protocols incorporating sensor-based reaction systems and VR stimuli were associated with measurable adaptations in dynamic visuomotor processing while preserving fundamental binocular vision parameters. Full article

Achieving high-accuracy and high-speed 3D shape measurement remains a significant challenge. This paper presents a novel technique using phase-order lines (POLs), which eliminates the need for phase unwrapping in a binocular system. By combining phase-shifting for high resolution and speckle projection for robust features, our method extracts POLs directly from the wrapped phase. The speckle patterns are then used to establish robust POL correspondences between stereo images. These matched POLs serve as reliable seeds to guide dense, sub-pixel matching directly on the wrapped phase, thus bypassing the complex phase unwrapping process. This approach significantly reduces the number of required patterns. The experimental results demonstrate that our method achieves a root-mean-square (RMS) error of 0.058 mm using only five patterns, delivering accuracy comparable to a 12-pattern temporal phase unwrapping (TPU) method while being significantly faster. Full article

Background: This review discusses the application of eye-tracking technology in the detection and monitoring of binocular vision anomalies among children. Methods: A scoping review using PRISMA guidelines was conducted through Scopus, ScienceDirect, and PubMed using the keywords “eye-tracking,” “binocular,” “vision,” “anomalies,” “paediatrics,” and “children” from 2015 to 2025. Studies excluded were not written in English, did not apply the eye tracker as a research tool, involved an ineligible population, or involved non-human subjects. Results: The search strategy identified 77 citations, yet only 14 studies met the inclusion criteria. This review revealed a variety of binocular vision anomalies detectable through eye-tracking systems, along with the specific models and parameters employed in these assessments. Application of eye-tracking technology in diagnosing conditions such as strabismus and amblyopia demonstrated potential for improved accuracy and early detection. Discussion: Eye-tracking technology demonstrates considerable potential for the detection and monitoring of binocular vision anomalies in children, particularly as a non-invasive method for early screening, thereby strengthening its clinical applicability. By assessing fixation stability, saccadic movements, and vergence responses, eye-tracking allows for the early detection of subtle visual anomalies, especially in the paediatric population. Conclusions: Eye-tracking technology represents a valuable advancement in paediatric vision care, enabling the more objective and earlier detection of binocular vision anomalies in the paediatric population. Full article

Detecting drivable areas is a fundamental task in autonomous driving systems. Although semantic segmentation networks have demonstrated strong performance in segmenting drivable regions, two key challenges persist. First, acquiring sufficient contextual information in complex road scenarios remains difficult, often leading to segmentation errors. Second, the coarseness of extracted features may degrade accuracy even when texture information is available in RGB images. To address these issues, we propose an enhanced DeepLabv3+ algorithm called Split Convolution Selective Attention Network (SCSANet), which incorporates the Adaptive Kernel (AK) and Split Convolution Attention (SCA) modules. AK adaptively adjusts the receptive field to accommodate varying road scenarios, while SCA improves boundary clarity by enhancing channel interaction. In addition, we employ surface normals to provide complementary geometric information, thereby strengthening the ability of the network to recognize drivable areas. To compensate for the lack of publicly available datasets for closed or semi-closed scenarios, we introduce XMUROAD, a new dataset of binocular disparity images. Experiments on the XMUROAD dataset demonstrate that the proposed architectural improvements yield an mIoU gain of 1.63% under the same RGB input, and the full pipeline with surface normal input achieves improvements of 1.55% to 2.59% in mF1 and 2.94% to 4.83% in mIoU over state-of-the-art methods. Experiments on the KITTI dataset further verify the generalization capability of SCSANet, with improvements of 1.58% in mF1 and 2.88% in mIoU over state-of-the-art methods. The proposed method provides a practical approach for accurate drivable area detection in closed and semi-closed mobile-robot scenarios. Full article

Line-structured light three-dimensional (3D) measurement is commonly used for three-dimensional contour reconstruction of objects in complex industrial environments, but the problem of missing information occurs when three-dimensional reconstruction is performed on objects with smooth surfaces, single texture, and high reflectivity, resulting in defective reconstructed object surfaces. For this reason, this study proposes a fused complementary 3D reconstruction technique based on a polarization-based binocular line-structured light system. First, the reconstructed image of the object is captured using a Polarization Binocular Camera, and the polarized imaging effectively reduces the strong highlights and extracts more detailed information on the surface of the object. Then, the calibrated camera and optical planes are used to acquire the spatial coordinates of the object reconstructed by the left camera and right camera. Finally, the spatial coordinates obtained by the left camera and right camera are aligned, and the high-precision 3D reconstruction results are generated. The experimental results show that the proposed method can effectively improve the accuracy and robustness of 3D reconstruction, has a good application prospect, and can meet the technical requirements of industrial 3D measurement. Full article

Accurate pose estimation is crucial for reliable docking and recovery of Autonomous Underwater Vehicles (AUVs). Traditional visual-based pose estimation methods face inherent challenges: monocular methods often struggle with depth inference, and conventional Perspective-n-Point (PnP) algorithms exhibit accuracy degradation at large viewing angles and limited noise resistance, while binocular systems involve higher computational complexity. This paper proposes a two-stage algorithm that combines iterative PnP initialization with binocular constraint optimization. By using iterative PnP to establish reliable initial estimates, the approach avoids convergence difficulties of direct binocular optimization, while the subsequent binocular refinement leverages stereo geometric constraints to enhance accuracy. Comprehensive evaluation through simulation, land-based experiments, and underwater validation demonstrates consistent performance improvements over conventional geometric methods. In simulation experiments across $-60°$ to $60°$ yaw angles, the method achieves 93.2% and 28.6% improvements in translation and rotation accuracy respectively compared to iterative PnP. Land-based validation confirms 32.7% average rotation error reduction, while underwater experiments demonstrate 76.5% average distance error reduction under real optical conditions including refraction and light attenuation. The method maintains real-time processing capability (2.16 ms per frame), offering a practical solution for AUV pose estimation in docking applications. Full article

Camera calibration is an essential research direction in photonics and computer vision. It achieves the standardization of camera data by using intrinsic and extrinsic parameters. Recently, RGB-D cameras have been an important device by supplementing deep information, and they are commonly divided into three kinds of mechanisms: binocular, structured light, and Time of Flight (ToF). However, the different mechanisms cause calibration methods to be complex and hardly uniform. Lens distortion, parameter loss, and sensor degradation et al. even fail calibration. To address the issues, we propose a camera calibration method based on the Expectation–Maximization (EM) algorithm. A unified model of latent variables is established for the different kinds of cameras. In the EM algorithm, the E-step estimates the hidden intrinsic parameters of cameras, while the M-step learns the distortion parameters of the lens. In addition, the depth values are calculated by the spatial geometric method, and they are calibrated using the least squares method under an optical motion capture system. Experimental results demonstrate that our method can be directly employed in the calibration of monocular and binocular RGB-D cameras, reducing image calibration errors between 0.6 and 1.2% less than least squares, Levenberg–Marquardt, Direct Linear Transform, and Trust Region Reflection. The deep error is reduced by 16 to 19.3 mm. Therefore, our method can effectively improve the performance of different RGB-D cameras. Full article

No-reference stereoscopic image quality assessment (NR-SIQA) remains a fundamental challenge due to the complex biological mechanisms of binocular rivalry and fusion, particularly under asymmetric distortions. In this paper, we propose a novel framework termed Multi-Stage Complementary Ensemble (MSCE). The core innovation lies in the Adaptive Selective Propagation (ASP) strategy embedded within a hierarchical Transformer architecture to dynamically regulates the fusion of binocular features. Specifically, by simulating the human visual system’s transition from binocular rivalry to fusion, the ASP strategy applies nonlinear gain control to selectively reinforce features from the governing view based on binocular discrepancies. Furthermore, the proposed Hierarchical Complementary Fusion (HCF) module effectively captures and integrates low-level texture integrity, mid-level structural degradation, and high-level semantic consistency, leveraging ensemble learning principles, within a unified quality-aware manifold. Experimental results on four benchmark datasets demonstrate that the MSCE framework achieves state-of-the-art performance, particularly in terms of prediction consistency under complex asymmetric distortions. Full article

Background: Acquired brain injury (ABI) often disrupts binocular vision, causing deviations on the cover test and reduced stereopsis that impair functional visual performance. This study investigated the effects of a dichoptic vision therapy protocol—based on an immersive virtual reality (VR) system—on visual field parameters, oculomotor reaction times, and self-reported visual symptoms in adults with ABI. Methods: In a controlled parallel-group design, adult ABI patients (median age 51 years) were assigned to an experimental group (dichoptic VR therapy) or a control group. Six sessions of visual therapy were performed. Primary outcomes included perimetric visual field indices and oculomotor reaction times; the secondary outcome was the Brain Injury Vision Symptom Survey (BIVSS) score. Etiology (stroke vs. traumatic brain injury) was recorded. Results: No statistically significant improvements were found in perimetric visual field indices (p > 0.05), except for a slight gain in the top-right quadrant in the experimental group. Reaction times did not differ significantly between groups. However, the experimental group reported a greater reduction in visual symptoms as measured by the BIVSS. Patients with traumatic brain injury exhibited better functional improvement, particularly in the top-left quadrant (p = 0.04). Conclusions: Dichoptic VR-based therapy did not restore perimetric field losses in ABI patients but reduced visual symptoms and may enhance functional adaptation of residual vision rather than structural recovery. The therapeutic response varied by etiology, favoring traumatic brain injury. Larger, longer trials integrating objective and subjective measures, including neuroimaging, are warranted. Full article

To address the bottlenecks of traditional jaw crusher liner wear detection—high safety risks, insufficient precision, and limited full-range analysis—this paper proposes a non-contact, high-precision wear analysis method based on binocular vision and deep learning. At its core is the integration of the state-of-the-art FoundationStereo zero-shot stereo matching algorithm, following scenario-specific adaptations, into the 3D reconstruction of industrial liners for wear analysis. A novel wear quantification methodology and corresponding indicator system are also proposed. After calibrating the ZED2 binocular camera and fine-tuning the algorithm, FoundationStereo achieves an Endpoint Error (EPE) of 0.09, significantly outperforming traditional algorithms. To meet on-site efficiency requirements, a “single-view rapid acquisition + CUDA engineering acceleration” strategy is implemented, reducing point cloud generation latency from 165 ms to 120 ms by rewriting kernel functions and optimizing memory access patterns. Geometric accuracy verification shows a Mean Absolute Error (MAE) ≤ 0.128 mm, fully meeting industrial measurement standards. A complete process of “3D reconstruction–model registration–quantitative analysis” is constructed, utilizing three core indicators (maximum wear depth, average wear depth, and wear area ratio) to characterize liner wear. Statistical results—such as an average maximum wear depth of 55.05 mm—are highly consistent with manual inspection data, providing a safe, efficient, and precise digital solution for the predictive maintenance and intelligent operation and maintenance (O&M) of liners. Full article

Background: We report an uncommon presentation of Lyme disease and highlight the importance of a detailed history in a patient with new-onset sixth nerve palsy. Methods: Case report and literature review. Results: A 46-year-old man receiving infliximab presented to the ophthalmology emergency department with horizontal binocular diplopia. History revealed a diffuse headache that had begun three weeks earlier. Ophthalmologic examination demonstrated a left sixth cranial nerve palsy. The workup showed positive Borrelia serum IgG, which was interpreted as a likely false-positive result given the limited specificity of serologic testing. At follow-up, the patient reported left-sided peripheral facial palsy, and worsening headache and diplopia. Further history revealed prior erythema migrans treated with doxycycline four months earlier. Considering these new findings, a lumbar puncture was performed and demonstrated intrathecal production of Borrelia antibodies. Neuroborreliosis, a neurologic involvement secondary to systemic infection by the spirochete Borrelia burgdorferi, was diagnosed. The patient was treated with oral doxycycline for 28 days with complete resolution of symptoms. Conclusions: Lyme disease may present with progressive neuro-ophthalmologic symptoms, underscoring the crucial role of ophthalmologists in its diagnosis. Moreover, immunosuppression may delay diagnosis and allow neurological progression, highlighting the need for careful history taking and close follow-up. Full article

The field of study on intimate partner violence has long been characterized by a bitter debate between the following two opposing theoretical and ideological positions on the nature of the phenomenon: the first is typical of the feminist perspective and considers IPV as an expression of gender-based violence; the second is typical—among others—of the attachment-based perspective and maintains that IPV would be a neutral form of violence with respect to gender. The aim of this contribution is to try to show how it is possible to make a more heuristically fruitful comparison between these two antagonistic perspectives, shifting the focus on the conceptual frameworks that underlie them and on their two different corresponding key explanatory concepts as follows: on the one hand, gender-based power on which the feminist perspective hinges, and on the other, love and love-related emotional dynamics on which the attachment-based perspective focuses. Finally, we will argue how these two key explanatory concepts can be kept combined in a sort of binocular vision and integrated into a more complex “power-and-love” explanatory framework. To this end, we will refer to a systemic approach to IPV, in particular to the contribution of Virginia Goldner, who proposes a model based on the close interconnection between power dynamics and love-related dynamics in the genesis and perpetuation of male violence in heterosexual intimate relationships. Full article

Background/Purpose: Four patients independently reported episodes of seeing a dimly flickering overlay on an otherwise intact part of their binocular visual field. The aim of the study was to describe the clinical characteristics of this episodic phenomenon, which we call dim flicker. Methods: Retrospective chart review and patient evaluation of an animated reference simulation. Results: The patients described repeated episodes of a seeing a patch of rhythmically oscillating dim flicker overlaid on a circumscribed patch of their otherwise normal binocular visual field. The flicker was typically seen at low ambient light levels and disappeared in bright light or when one or both eyes were covered. Episodes lasted seconds to minutes. Some flicker patches crossed the vertical midline. The flicker was subjectively experienced as coming from one specific eye. Compared to a 7 Hz flicker simulation, patients reported differences in location, prominence, and frequency, with the latter ranging from 3 to 10 Hz. In three patients, the flicker was sometimes experienced during aerobic exercise and in two patients sometimes when they rose at night in the dark. In one patient, the flicker corresponded to an area of ischemic macular edema secondary to central retinal vein occlusion. There was no headache during or after the flicker. Associated maladies included retinal venous congestion, central serous chorioretinopathy, arterial hypertension, atrial fibrillation, and migraine with visual aura distinctly different from the dim flicker. Conclusions: Episodes of seeing an endogenous, rhythmically oscillating transparent overlay within a confined, non-expanding part of an otherwise intact binocular visual field appears to be a distinct nosological entity that can be associated with ocular and systemic vascular disease. Full article

Mango is the second most widely cultivated tropical fruit in the world. Its harvesting mainly relies on manual labor. During the harvest season, the hot weather leads to low working efficiency and high labor costs. Current research on automatic mango harvesting mainly focuses on locating the fruit stem harvesting point, followed by stem clamping and cutting. However, these methods are less effective when the stem is occluded. To address these issues, this study first acquires images of four mango varieties in a mixed cultivation orchard and builds a dataset. Mango detection and occlusion-state classification models are then established based on YOLOv11m and YOLOv8l-cls, respectively. The detection model achieves an AP_0.5–0.95 (average precision at IoU = 0.50:0.05:0.95) of 90.21%, and the accuracy of the classification model is 96.9%. Second, based on the mango growth characteristics, detected mango bounding boxes and binocular vision, we propose a spatial localization method for the mango grasping point. Building on this, a mango-grasping and stem-cutting end-effector is designed. Finally, a mango harvesting robot system is developed, and verification experiments are carried out. The experimental results show that the harvesting method and procedure are well-suited for situations where the fruit stem is occluded, as well as for fruits with no occlusion or partial occlusion. The mango grasping success rate reaches 96.74%, the stem cutting success rate is 91.30%, and the fruit injury rate is less than 5%. The average image processing time is 119.4 ms. The results prove the feasibility of the proposed methods. Full article

Inspecting the inner walls of large pressure vessels requires accurate weld seam recognition, complete coverage, and precise path tracking, particularly in low-feature environments. This paper presents a fully autonomous mobile robotic system that integrates weld seam detection, localization, and tracking to support ultrasonic testing. An improved Differentiable Binarization Network (DBNet) combined with the Spatially Variant Transformer (SVTR) model enhances digital stamp recognition, while weld paths are reconstructed from three-dimensional position data acquired via binocular stereo vision. To ensure complete traversal and accurate tracking, a global–local hierarchical planning strategy is implemented: the A-star (A*) algorithm performs global path planning, the Rapidly Exploring Random Tree Connect (RRT-Connect) algorithm handles local path generation, and point cloud normal–based spherical interpolation produces smooth tracking trajectories for robotic arm motion control. Experimental validation demonstrates a 94.7% digital stamp recognition rate, 95.8% localization success, 1.65 mm average weld tracking error, 2.12° normal fitting error, 98.2% seam coverage, and a tracking speed of 96 mm/s. These results confirm the system’s capability to automate weld seam inspection and provide a reliable foundation for subsequent ultrasonic testing in pressure vessel applications. Full article