Monocular Vision Research Articles

Effects of camera external parameters error on measurement accuracy in monocular vision

Monocular vision is widely employed in industrial measurement scenarios due to its low cost, flexibility, mature algorithms, and high reliability. However, in actual production line monocular vision measurement systems, the measured plane may be affected by motion mechanisms or device vibrations, causing it to deviate from the system calibration plane and resulting in measurement errors. Current research primarily focuses on analyzing the influence of camera internal parameters and feature extraction algorithms on measurement errors, with limited quantitative analysis of the impact of camera external parameters. To address this issue, our paper derives a mathematical expression for measurement error when rotational and translational motion occurs between the measurement and calibration planes. Theoretical analysis reveals that when the camera optical axis is perpendicular to the measurement plane, measurement error is independent of the main point coordinates of the camera’s optical axis, translation component in the measurement plane, and rotation angle around the camera’s optical axis. Instead, it exhibits a linear relationship with the translation component in the direction of the camera’s optical axis and is inversely proportional to the normalized focal length of the camera. When the optical axis of the camera is not perpendicular to the calibration plane, the measurement error exhibits a nonlinear relationship with camera’s internal and external parameters. To verify our theoretical derivation’s accuracy, we conduct measurement experiments using both industrial and telecentric lenses and analyzed rotation and translation of the measured plane separately. The measurement data was evaluated by Root Mean Square Error and Pearson Correlation Coefficient, which demonstrates that experimental and theoretical function images exhibit consistent trends, verifying our theoretical derivation’s correctness and providing a theoretical guide for improving actual visual measurement accuracy.

RUPTURED RETINAL ARTERIAL MACROANEURYSMS ASSOCIATED WITH HEMORRHAGIC BACILLARY LAYER DETACHMENTS.

Bacillary layer detachments (BALAD) are a recently recognized form of retinal detachment involving a splitting of photoreceptors at the inner segment myoid zone, with separation of the external limiting membrane and ellipsoid zone on optical coherence tomography (OCT). A growing number of disease processes are recognized to cause BALAD, and here we present three of the first cases of hemorrhagic retinal artery macroaneurysms that resulted in BALAD. A retrospective review of three patients who presented for acute, painless, monocular vision loss was performed. Multimodal imaging including fundus photography and OCT are included in this analysis. Three elderly female patients, all with a history of hypertension, presented with ruptured macroaneurysms involving the macula. All three patients had evidence of BALAD on OCT. Various management strategies were used. Hemorrhagic retinal arterial macroaneurysms can be associated with BALAD, observed best on OCT. This is most likely secondary to the rapid accumulation of intraretinal fluid during the hemorrhage, which leads to an avulsion at the inner segment myoid zone-a site of inherent structural weakness in the photoreceptors. Visual recovery may be improved in instances of hemorrhagic macroaneurysms associated with BALAD, similar to other disease entities where BALAD occurs, although further research is needed.

Binocular function in the aging visual system: fusion, suppression, and stereoacuity.

Changes in vision that occur in normal healthy aging can be seen in fundamental measures of monocular vision. However, the nature of the changes in binocular vision with age remain unclear. A total of 28 older (53-66 years) and 28 younger adults (20-31 years) were enrolled in this study. We performed a battery of tests to assess differences in monocular contrast thresholds and various binocular visual functions including dichoptic masking weight and strength, the binocular balance point for fused stimuli, and stereoacuity in the aging and control groups. Aging significantly increased monocular contrast thresholds (p < 0.001). Although this suggests that aging reduces the effective "input gain" to vision, we also found a significantly elevated contribution of those weaker signals to interocular suppression (p < 0.001). Consequently, there was no significant net difference in the strength of interocular suppression (p = 0.065). We did not find a significant difference of absolute balance point between the two groups (p = 0.090). Lastly, the mean stereoacuity was worse in the older group compared to the younger group (p = 0.002). Our findings confirm previous results showing differences in contrast sensitivity and stereoacuity with aging. Furthermore, we find a change in interocular suppression that is a possible consequence of the change in contrast sensitivity. It is suggestive of a cortical system that maintains a homeostatic balance in interocular suppression across the lifespan.

Pose Measurement Method Based on Machine Vision and Novel Directional Target

Aiming at the shortcomings of the existing machine vision pose measurement technology, a pose measurement method based on monocular vision and a cooperative target is proposed. A planar target designed with circles and rings as the main body is dedicated to object pose measurement, and a feature point coordinate extraction and sorting algorithm is designed for this target to effectively extract image features on the target. The RANSAC algorithm and topology-based fitting for the intersection method are used to optimise data processing, further improving the accuracy of feature point coordinate extraction and ultimately achieving high-precision measurement of object poses. The experimental results show that the measurement accuracy of the roll angle perpendicular to the optical axis can reach 0.02°, and the repeatability can reach 0.0004° after removing the systematic error; the measurement accuracy of the pitch angle can reach 0.03°, and the repeatability can go to 0.002° after removing the systematic error. The measurement range of the pitch angle is [−30°, +30°]; the measurement range of the roll angle is [−179°, +179°]. The experimental results show that the system has high measurement accuracy and meets the requirements of high-precision measurement.

MoNA Bench: A Benchmark for Monocular Depth Estimation in Navigation of Autonomous Unmanned Aircraft System

Efficient trajectory and path planning (TPP) is essential for unmanned aircraft systems (UASs) autonomy in challenging environments. Despite the scale ambiguity inherent in monocular vision, characteristics like compact size make a monocular camera ideal for micro-aerial vehicle (MAV)-based UASs. This work introduces a real-time MAV system using monocular depth estimation (MDE) with novel scale recovery module for autonomous navigation. We present MoNA Bench, a benchmark for Monocular depth estimation in Navigation of the Autonomous unmanned Aircraft system (MoNA), emphasizing its obstacle avoidance and safe target tracking capabilities. We highlight key attributes—estimation efficiency, depth map accuracy, and scale consistency—for efficient TPP through MDE.

Configuration optimization method of cooperative target for pose estimation with monocular vision

Configuration optimization method of cooperative target for pose estimation with monocular vision

A Remote Consult Retinal Artery Occlusion Diagnostic Protocol

To report a novel protocol for diagnosis of retinal artery occlusions at the point of care using OCT and a remote consult model. Retrospective case series and evaluation of a diagnostic test or technology. Adult patients who presented with painless monocular vision loss and were diagnosed with a nonarteritic retinal artery occlusion. OCT machines were placed in the stroke center or emergency department at 3 hospitals within our health system. Patients who presented with painless monocular vision loss were evaluated by the stroke neurology service and an OCT was acquired. The images were interpreted remotely by the retina service. An in-house ophthalmology consult was not required to make the final treatment decision. Eligible patients were treated with intra-arterial tissue plasminogen activator (IA-tPA). Patients were followed by ophthalmology during their admission when an in-house consultation service was available or otherwise evaluated immediately after discharge. Visual acuity (VA) before and after treatment with IA-tPA; time from last known well (LKW) to treatment; and time from presentation to treatment. In the first 18 months since the protocol went live, 59 patients were evaluated. Twenty-five patients (42%) had a confirmed retinal artery occlusion based on OCT and follow-up examination. Ten patients were eligible for treatment, and 9 patients received treatment with IA-tPA. There was a statistically significant improvement in mean VA from logarithm of the minimum angle of resolution (logMAR) 2.14 to logMAR 0.7 within 24 hours after treatment (P= 0.0001) and logMAR 1.04 after 4 weeks (P= 0.01). Clinically significant improvement was noted in 66% of patients within 24 hours and maintained through 1 month in 56% of all treated patients. The mean time to treatment from LKW was 543 minutes and from presentation at the stroke center was 146 minutes. We report the successful implementation of a remote consult protocol using point-of-care automated OCT. This novel paradigm demonstrates the potential utility of remote consult services for the diagnosis of time-sensitive ophthalmic emergencies. Proprietary or commercial disclosure may be found after the references.

Train Distance Estimation for Virtual Coupling Based on Monocular Vision.

By precisely controlling the distance between two train sets, virtual coupling (VC) enables flexible coupling and decoupling in urban rail transit. However, relying on train-to-train communication for obtaining the train distance can pose a safety risk in case of communication malfunctions. In this paper, a distance-estimation framework based on monocular vision is proposed. First, key structure features of the target train are extracted by an object-detection neural network, whose strategies include an additional detection head in the feature pyramid, labeling of object neighbor areas, and semantic filtering, which are utilized to improve the detection performance for small objects. Then, an optimization process based on multiple key structure features is implemented to estimate the distance between the two train sets in VC. For the validation and evaluation of the proposed framework, experiments were implemented on Beijing Subway Line 11. The results show that for train sets with distances between 20 m and 100 m, the proposed framework can achieve a distance estimation with an absolute error that is lower than 1 m and a relative error that is lower than 1.5%, which can be a reliable backup for communication-based VC operations.

Epidemiological and clinical characteristics of open globe injuries in Southwest China.

Open globe injuries (OGIs) are one of the leading causes of monocular vision loss, and the clinical characteristics of OGIs are region specific. The features and patterns of OGIs in Southwest China are poorly known and not well studied. Our study aimed to review the epidemiological and clinical characteristics of patients hospitalized for OGIs in Southwest China. A retrospective study of OGI patients admitted to the West China Hospital from January 1st, 2015, to December 31st, 2019, was performed. Demographic characteristics and injury details were recorded. The Birmingham Eye Trauma Terminology system and the ocular trauma score (OTS) were used. A total of 3,014 patients were included. The male-to-female ratio was 5.2:1, and the mean age was 35.6 ± 19.1 years. 15.2% of patients were from the ethnic groups. The highest-risk occupation was the farmer (30.3%), followed by the worker (28.5%). OGIs occurred more frequently in people with middle (37.0%) and primary school (33.1%) education levels. Types of injuries included 46.8% penetration, 21.2% rupture, 2.9% perforation, and 29.1% intraocular foreign body (IOFB). The injuries types differed between age and occupation groups (p < 0.001). IOFBs had a higher risk of causing endophthalmitis, retinal detachment, and traumatic cataracts (p < 0.001). The most common injuries resulted from sharp objects (72.7%). The causes of the injuries were significantly associated with age, ethnicity, and occupation (p < 0.001). Explosion injuries and attacks by animals were more common among people of Tibetan and Yi ethnicities. Blunt trauma, vehicle crashes, falls and age older than 60 years were risk factors for a lack of light perception and lower OTS scores prognosis. OGIs in Southwest China mainly affected working-aged males, especially workers or farmers. Severe vision loss and IOFBs are more common findings. OGIs in older patients and ethnic minorities requires additional attention.

Fusion of Time-of-Flight Based Sensors with Monocular Cameras for a Robotic Person Follower

Human-robot collaboration (HRC) is becoming increasingly important in advanced production systems, such as those used in industries and agriculture. This type of collaboration can contribute to productivity increase by reducing physical strain on humans, which can lead to reduced injuries and improved morale. One crucial aspect of HRC is the ability of the robot to follow a specific human operator safely. To address this challenge, a novel methodology is proposed that employs monocular vision and ultra-wideband (UWB) transceivers to determine the relative position of a human target with respect to the robot. UWB transceivers are capable of tracking humans with UWB transceivers but exhibit a significant angular error. To reduce this error, monocular cameras with Deep Learning object detection are used to detect humans. The reduction in angular error is achieved through sensor fusion, combining the outputs of both sensors using a histogram-based filter. This filter projects and intersects the measurements from both sources onto a 2D grid. By combining UWB and monocular vision, a remarkable 66.67% reduction in angular error compared to UWB localization alone is achieved. This approach demonstrates an average processing time of 0.0183s and an average localization error of 0.14 meters when tracking a person walking at an average speed of 0.21 m/s. This novel algorithm holds promise for enabling efficient and safe human-robot collaboration, providing a valuable contribution to the field of robotics.

The influence of simulated visual impairment on distance stereopsis.

The intricate interrelationships between visual acuity (VA) and stereopsis depend on an array of factors, incorporating the nature of vision impairment, its manifestation (monocular versus binocular), and the classification of stereopsis test symbols used. The objectives of this study were to methodically dissect these multifaceted interactions by simulating a diverse range of vision loss conditions. Thirty medical students with normal vision were subjected to simulated vision loss through opacification and blurring methodologies. Stereopsis was assessed at a distance using both contour-based and random-dot-based symbols under equal binocular and varied monocular VA conditions. In this study, opacification consistently affected stereopsis more than blurring at equivalent VA reductions. However, this difference was absent in contour-based symbols under binocular vision impairment conditions. Significant differences in stereopsis emerged between monocular and binocular vision within the opacification contour-based groups. These differences were less evident in the opacification and blurring groups using random-dot-based patterns. In terms of symbols, the contour-based test demonstrated superior results to the random-dot-based test, particularly under decreased VA. In sum, the method of VA reduction and the choice of stereogram significantly impact distance stereopsis outcomes. This understanding can guide clinical assessments of stereopsis in individuals with varying visual impairments.

Abstract WMP56: Diagnosis of Acute Central Retinal Artery Occlusion With a Nonmydriatic Ocular Fundus Camera Combined With Optical Coherence Tomography in the Emergency Department: A New Paradigm

Background: Central retinal artery occlusion (CRAO) is a retinal infarction with causes/management similar to cerebral infarction. However, CRAO diagnosis is often delayed, resulting in missed opportunities for rapid treatment. Diagnosis by ophthalmologists is essential prior to management by stroke neurologists and may be challenging within a few hours of vision loss. Our goal is to provide a new paradigm in the emergency department (ED) with the implementation of a nonmydriatic ocular fundus camera (NMFP) combined with optical coherence tomography (OCT) to allow for ultrarapid remote diagnosis and stroke alert as soon as patients present to the ED. Methods: Prospective collection of data from consecutive patients who had NMFP-OCT for acute monocular vision loss in our general ED affiliated with a comprehensive stroke center. We collected timing of photographs; final diagnosis (CRAO/other causes of vision loss); time between vision loss onset and CRAO diagnosis; NMFP-OCT findings. Results: Over 9 weeks, 27 patients had NMFP-OCT obtained for acute monocular visual loss, including 9 CRAO [others included 7 retinal detachments; 8 vitreous hemorrhages; 3 temporal arteritis]. Diagnosis of acute CRAO was made remotely on NMFP-OCT obtained 30, 33, 36 min after arriving in ED in 3 patients presenting to ED within 3.5 hrs of vision loss. In all 3 patients, the ocular color photographs were almost normal and acute CRAO diagnosis was made primarily from the OCT showing inner retinal edema/hyperreflectivity. Conclusion: Incorporating NMFP-OCT into the ED workflow can be used as a substitute for funduscopic examination/pupillary dilation, allowing for remote diagnosis of CRAO by ophthalmologists who can provide real time recommendations before in person visit. These positive preliminary results suggest that this strategy accelerates the diagnosis of urgent vision loss, resulting in improved patient outcomes. Results of the first 6 months will be presented at the conference.

Vision-based collective motion: A locust-inspired reductionist model.

Naturally occurring collective motion is a fascinating phenomenon in which swarming individuals aggregate and coordinate their motion. Many theoretical models of swarming assume idealized, perfect perceptual capabilities, and ignore the underlying perception processes, particularly for agents relying on visual perception. Specifically, biological vision in many swarming animals, such as locusts, utilizes monocular non-stereoscopic vision, which prevents perfect acquisition of distances and velocities. Moreover, swarming peers can visually occlude each other, further introducing estimation errors. In this study, we explore necessary conditions for the emergence of ordered collective motion under restricted conditions, using non-stereoscopic, monocular vision. We present a model of vision-based collective motion for locust-like agents: elongated shape, omni-directional visual sensor parallel to the horizontal plane, and lacking stereoscopic depth perception. The model addresses (i) the non-stereoscopic estimation of distance and velocity, (ii) the presence of occlusions in the visual field. We consider and compare three strategies that an agent may use to interpret partially-occluded visual information at the cost of the computational complexity required for the visual perception processes. Computer-simulated experiments conducted in various geometrical environments (toroidal, corridor, and ring-shaped arenas) demonstrate that the models can result in an ordered or near-ordered state. At the same time, they differ in the rate at which order is achieved. Moreover, the results are sensitive to the elongation of the agents. Experiments in geometrically constrained environments reveal differences between the models and elucidate possible tradeoffs in using them to control swarming agents. These suggest avenues for further study in biology and robotics.

Automatic Outer Contour Detection and Quantification of Vehicles Using Monocular Vision

Oversized vehicles have the potential to collide with walls or ceilings when passing through tunnels and bridges, posing a serious threat to the health of transportation infrastructure and public safety. Hence, it is crucial to accurately and immediately detect vehicle dimensions, including length, width, and height, to avoid such accidents. Using computer vision and view geometry, this study presents a framework for automatically detecting and quantifying the outer contours of vehicles through monocular vision. First, traffic scene images are captured which are then used to create a transformation matrix of the ground surface. Second, a modified Mask region-based convolutional neural network (Mask R-CNN) is constructed to detect and segment the vehicle instances from the video frames. Finally, a view geometry-based algorithm was developed to detect the outer contours of passing vehicles and quantify their dimensions. In the field test, the accuracy of the vehicle segmentation and the identified vehicle dimensions was validated. In addition, the proposed method’s superiority was confirmed by comparing it with two other existing approaches. The comparison results show that the proposed method has better accuracy and is more convenient to use since it does not require a premeasured reference. In addition, the developed method can accurately identify not only the dimensions of vehicles parallel to the road but also vehicles that are changing lanes or making a U-turn.

A laser-assisted depth detection method for underwater monocular vision

A laser-assisted depth detection method for underwater monocular vision

Self-calibrating technique for 3D displacement measurement using monocular vision and planar marker

Although the vision-based displacement measurement of structures has been widely studied for decades, it still poses challenges for practical applications, including the issues of calibration and automatic long-term monitoring. This paper introduces a monocular-vision based self-calibrating technique for accurately measuring the 3D structural displacement. The technique utilizes a tailor-made planar marker with unique graph patterns, enabling precise image recognition and PnP resolution. The proposed technique automatically estimates the 3D position and 3D orientation of the marker. The limitations of marker-free techniques in terms of long-term monitoring have also been discussed. The accuracy and robustness of the proposed technique are systematically examined by Monte-Carlo simulation, and then verified by experiments. Results show that accuracy of the proposed technique for 3D displacement measurement is 0.049 mm, which indicates the effectiveness of the technique for automatically measuring and calibrating stereo displacement of structures using monocular vision.

Measurement of Spherical Particle Pose by Monocular Vision

Measurement of Spherical Particle Pose by Monocular Vision

A Novel Method for Measuring the Attitude Angles of the Artillery Barrel Based on Monocular Vision

A Novel Method for Measuring the Attitude Angles of the Artillery Barrel Based on Monocular Vision

Research on measurement technology of rocket recovery height based on monocular vision

Research on measurement technology of rocket recovery height based on monocular vision

Reconstruction of Dynamic Human Neural Radiance Fields Based on Monocular Vision

Reconstruction of Dynamic Human Neural Radiance Fields Based on Monocular Vision