[Mobile device-based childhood vision screening for early detection of amblyopia]

Bevezetés: Az amblyopia vagy tompalátás binokuláris eredetű fejlődési zavar, amelyet a legtöbbször egy szemet érintő, lencsével nem korrigálható látásromlásként definiálnak. Magas prevalenciájával világszerte népegészségügyi problémát jelent, így a kisgyermekkori látásszűrések fontos célja az amblyopia megelőzése. Célkitűzés: Célunk egy mobilapplikáció-alapú térlátásvizsgáló teszt (EuvisionTab® sztereoteszt, ETS) értékelése, mellyel a tompalátás és rizikófaktorai (kancsalság, törési hibák) időben kiszűrhetők. Módszer: Vizsgálataink során nemzetközileg ismert klinikai sztereoteszteket (Lang II, TNO, Stereo Fly, Frisby) hasonlítottunk össze az EuvisionTab sztereoteszt különböző verzióival gyermekek körében (n = 453, átlagéletkor: 7,45 év). A random pontokból álló EuvisionTab sztereoteszt esetén 4 különböző beállítást alkalmaztunk, a dinamizmust, a pontsűrűséget (denzitást), illetve a vizuális zajt változtatva. A tesztek hatékonyságát ’receiver-operating characteristic’ (ROC) módszerrel értékeltük, melynek legfontosabb mérőszáma a görbe alatti terület (AUC). Eredmények: Az EuvisionTab sztereotesztek nagy szenzitivitásúnak bizonyultak a klasszikus klinikai tesztekhez viszonyítva, specificitásuk viszont több esetben elmaradt tőlük. Az amblyopia esetében a legjobb szenzitivitást (91%) a kis denzitású, vizuális zajt tartalmazó dinamikus teszt érte el, míg a legjobb specificitásértéket (89%) a statikus nagy denzitású esetében kaptuk. A hagyományos klinikai tesztek közül a legjobb szenzitivitással (88%) a TNO rendelkezett, míg a legjobb specificitással (98%) a Lang-teszt. A ROC-analízis alapján minden alkalmazott sztereoteszt jó vagy kiválóan alkalmas (ROC-AUC>0,80) az amblyopia szűrésére, míg a kancsalság esetén a TNO, a Stereo Fly, valamint az EuvisionTab tesztek feleltek meg ennek a kritériumnak. Következtetés: Az EuvisionTab sztereotesztek megfelelőnek bizonyultak az amblyopia szűrésére, nagy szenzitivitással rendelkeznek. A módszer további előnyei a véletlenszerű ingersorozat, a rugalmas paraméterbeállítások, a statisztikai alapú döntéshozatal, a kényelmes dokumentáció, valamint a könnyű és gyors kivitelezhetőség. Ezek alapján a legmodernebb látásszűrési protokoll részévé válhat. Orv Hetil. 2024; 165(16): 620–628.

Temporal mechanisms in frontoparallel stereomotion revealed by individual differences analysis

Masking experiments, using vertical and horizontal sinusoidal depth corrugations, have suggested the existence of more than two spatial-frequency disparity mechanisms. This result was confirmed through an individual differences approach. Here, using factor analytic techniques, we want to investigate the existence of independent temporal mechanisms in frontoparallel stereoscopic (cyclopean) motion. To construct stereomotion, we used sinusoidal depth corrugations obtained with dynamic random-dot stereograms. Thus, no luminance motion was present monocularly. We measured disparity thresholds for drifting vertical (up-down) and horizontal (left-right) sinusoidal corrugations of 0.4 cyc/deg at 0.25, 0.5, 1, 2, 4, 6, and 8 Hz. In total, we tested 34 participants. Results showed a small orientation anisotropy with lower thresholds for horizontal corrugations. Disparity thresholds as a function of temporal frequency were almost constant from 0.25 up to 1 Hz, and then they increased monotonically. Principal component analysis uncovered two significant factors for vertical and two for horizontal corrugations. Varimax rotation showed that one factor loaded from 0.25 to 1-2 Hz and a second factor from 2 to 4 to 8 Hz. Direct Oblimin rotation indicated a moderate intercorrelation of both factors. Our results suggest the possible existence of two somewhat interdependent temporal mechanisms involved in frontoparallel stereomotion.

Measurement Method for Contact Wire Wear Based on Stereovision

The contact wire wear is an important parameter to ensure the safety operation of electric railways. The contact wire may break if the wear is serious, which leads to transportation interruptions. This study proposes an optical measurement method of contact wire wear, using stereovision technology. The matching method of stereovision based on line-scan cameras is proposed. A lookup-table method is developed to exactly determine the image resolution caused by the contact wire being in different spatial positions. The wear width of the contact wire is extracted from catenaries' images, and the residual thickness of the contact wire is calculated. The method was verified by field tests. The round-robin tests of the residual thickness at the same location present excellent measurement repetitiveness. The maximum difference value between dynamic test results and ground measurement results is 0.13 mm. This research represents a potential way to implement condition-based maintenance for contact wire wear in the future in order to improve the maintenance efficiency and ensure the safety of catenary infrastructure.

A New Principle toward Robust Matching in Human-like Stereovision

Visual signals are the upmost important source for robots, vehicles or machines to achieve human-like intelligence. Human beings heavily depend on binocular vision to understand the dynamically changing world. Similarly, intelligent robots or machines must also have the innate capabilities of perceiving knowledge from visual signals. Until today, one of the biggest challenges faced by intelligent robots or machines is the matching in stereovision. In this paper, we present the details of a new principle toward achieving a robust matching solution which leverages on the use and integration of top-down image sampling strategy, hybrid feature extraction, and Restricted Coulomb Energy (RCE) neural network for incremental learning (i.e., cognition) as well as robust match-maker (i.e., recognition). A preliminary version of the proposed solution has been implemented and tested with data from Maritime RobotX Challenge. The contribution of this paper is to attract more research interest and effort toward this new direction which may eventually lead to the development of robust solutions expected by future stereovision systems in intelligent robots, vehicles, and machines.

The eRDS v6 Stereotest and the Vivid Vision Stereo Test: Two New Tests of Stereoscopic Vision

Purpose

To describe two new stereoacuity tests: the eRDS v6 stereotest, a global dynamic random dot stereogram (dRDS) test, and the Vivid Vision Stereo Test version 2 (VV), a local or "contour" stereotest for virtual reality (VR) headsets; and to evaluate the tests' reliability, validity compared to a dRDS standard, and learning effects.

Methods

Sixty-four subjects passed a battery of stereotests, including perceiving depth from RDS. Validity was evaluated relative to a tablet-based dRDS reference test, ASTEROID. Reliability and learning effects were assessed over six sessions.

Results

eRDS v6 was effective at measuring small thresholds (<10 arcsec) and had a moderate correlation (0.48) with ASTEROID. Across the six sessions, test-retest reliability was good, varying from 0.84 to 0.91, but learning occurred across the first three sessions. VV did not measure stereoacuities below 15 arcsec. It had a weak correlation with ASTEROID (0.27), and test-retest reliability was poor to moderate, varying from 0.35 to 0.74; however, no learning occurred between sessions.

Conclusions

eRDS v6 is precise and reliable but shows learning effects. If repeated three times at baseline, this test is well suited as an outcome measure for testing interventions. VV is less precise, but it is easy and rapid and shows no learning. It may be useful for testing interventions in patients who have no global stereopsis.

Translational Relevance

eRDS v6 is well suited as an outcome measure to evaluate treatments that improve adult stereodepth perception. VV can be considered for screening patient with compromised stereovision.

Depth-Resolved Localization Microangiography in the NIR-II Window

Detailed characterization of microvascular alterations requires high-resolution 3D imaging methods capable of providing both morphological and functional information. Existing optical microscopy tools are routinely used for microangiography, yet offer suboptimal trade-offs between the achievable field of view and spatial resolution with the intense light scattering in biological tissues further limiting the achievable penetration depth. Herein, a new approach for volumetric deep-tissue microangiography based on stereovision combined with super-resolution localization imaging is introduced that overcomes the spatial resolution limits imposed by light diffusion and optical diffraction in wide-field imaging configurations. The method capitalizes on localization and tracking of flowing fluorescent particles in the second near-infrared window (NIR-II, ≈1000-1700 nm), with the third (depth) dimension added by triangulation and stereo-matching of images acquired with two short-wave infrared cameras operating in a dual-view mode. The 3D imaging capability enabled with the proposed method facilitates a detailed visualization of microvascular networks and an accurate blood flow quantification. Experiments performed in tissue-mimicking phantoms demonstrate that high resolution is preserved up to a depth of 4 mm in a turbid medium. Transcranial microangiography of the entire murine cortex and penetrating vessels is further demonstrated at capillary level resolution.

Neural Correlates of Sensory Eye Dominance in Human Visual White Matter Tracts

A significant proportion of the human neurotypical population exhibits some degree of sensory eye dominance (SED), referring to the brain's preferential processing of one eye's input versus another. The neural substrates underlying this functional imbalance are not well known. Here, we investigated the relationship between visual white matter tract properties and SED in the human neurotypical population. Observers' performance on two commonly used dichoptic tasks were used to index SED, along with performance on a third task to address a functional implication of binocular imbalance: stereovision. We show that diffusivity metrics of the optic radiations (ORs) well predict behavioral SED metrics. We found no relationship between SED and stereosensitivity. Our data suggest that SED is not simply reflected by gray matter structural and functional alterations, as often suggested, but relates, at least in part to the microstructural properties of thalamocortical white matter.

Automatic landmark identification for surgical 3d-navigation - A proposed method for marker-free dental surgical navigation systems

This paper proposes a conceptual method to calculate the pose of a stereo-vision camera relative to an artificial mandible without additional markers. The general method for marker-free navigation has four steps: 1) parallel image acquisition by a stereo-vision camera, 2) automatic identification of 2d point pairs (landmark pairs) in a left and a right image, 3) calculation of related 3d points in the joint camera coordinate system and 4) matching of 3d points generated to a preoperative 3d model (i.e., CT data based). To identify and compare landmarks in the acquired stereo images, well-known algorithms for landmark detection, description and matching were compared within the developed approach. Finally, the BRISK algorithm (Leutenegger S, Chli M, Siegwart RY. BRISK: Binary Robust invariant scalable keypoints. Proceedings of the IEEE International Conference on Computer Vision; 2011: 2548-2555) was used. The proposed method was implemented in MATLAB^® and validated in vitro with one artificial mandible. The accuracy evaluation of the camera positions calculated resulted in an average deviation error of 1.45 mm ± 0.76 mm to the real camera displacement. This value was calculated using only stereo images with over 100 reconstructed landmark pairs each. This provides the basis for marker-free navigation.

Binocular mirror-symmetric microsaccadic sampling enables Drosophila hyperacute 3D vision

To move efficiently, animals must continuously work out their x,y,z positions with respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes’ optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes’ whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila superresolution three-dimensional vision and proposes neural computations for accurately predicting these flies’ depth-perception dynamics, limits, and visual behaviors.

Neural mechanisms behind stereopsis, which requires simultaneous disparity inputs from two eyes, have remained mysterious. Here we show how ultrafast mirror-symmetric photomechanical contractions in the frontal forward-facing left and right eye photoreceptors give Drosophila superresolution three-dimensional (3D) vision. By interlinking multiscale in vivo assays with multiscale simulations, we reveal how these photoreceptor microsaccades—by verging, diverging, and narrowing the eyes’ overlapping receptive fields—channel depth information, as phasic binocular image motion disparity signals in time. We further show how peripherally, outside stereopsis, microsaccadic sampling tracks a flying fly’s optic flow field to better resolve the world in motion. These results change our understanding of how insect compound eyes work and suggest a general dynamic stereo-information sampling strategy for animals, robots, and sensors.

Optics and neural adaptation jointly limit human stereovision

Stereovision is the ability to perceive fine depth variations from small differences in the two eyes' images. Using adaptive optics, we show that even minute optical aberrations that are not clinically correctable, and go unnoticed in everyday vision, can affect stereo acuity. Hence, the human binocular system is capable of using fine details that are not experienced in everyday vision. Interestingly, stereo acuity varied considerably across individuals even when they were provided identical perfect optics. We also found that individuals' stereo acuity is better when viewing with their habitual optics rather than someone else's (better) optics. Together, these findings suggest that the visual system compensates for habitual optical aberrations through neural adaptation and thereby optimizes stereovision uniquely for each individual. Thus, stereovision is limited by small optical aberrations and by neural adaptation to one's own optics.

A Runway Safety System Based on Vertically Oriented Stereovision

In 2020, over 10,000 bird strikes were reported in the USA, with average repair costs exceeding $200 million annually, rising to $1.2 billion worldwide. These collisions of avifauna with airplanes pose a significant threat to human safety and wildlife. This article presents a system dedicated to monitoring the space over an airport and is used to localize and identify moving objects. The solution is a stereovision based real-time bird protection system, which uses IoT and distributed computing concepts together with advanced HMI to provide the setup's flexibility and usability. To create a high degree of customization, a modified stereovision system with freely oriented optical axes is proposed. To provide a market tailored solution affordable for small and medium size airports, a user-driven design methodology is used. The mathematical model is implemented and optimized in MATLAB. The implemented system prototype is verified in a real environment. The quantitative validation of the system performance is carried out using fixed-wing drones with GPS recorders. The results obtained prove the system's high efficiency for detection and size classification in real-time, as well as a high degree of localization certainty.

Robust Stereo Visual Odometry Using Improved RANSAC-Based Methods for Mobile Robot Localization

In this paper, we present a novel approach for stereo visual odometry with robust motion estimation that is faster and more accurate than standard RANSAC (Random Sample Consensus). Our method makes improvements in RANSAC in three aspects: first, the hypotheses are preferentially generated by sampling the input feature points on the order of ages and similarities of the features; second, the evaluation of hypotheses is performed based on the SPRT (Sequential Probability Ratio Test) that makes bad hypotheses discarded very fast without verifying all the data points; third, we aggregate the three best hypotheses to get the final estimation instead of only selecting the best hypothesis. The first two aspects improve the speed of RANSAC by generating good hypotheses and discarding bad hypotheses in advance, respectively. The last aspect improves the accuracy of motion estimation. Our method was evaluated in the KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) and the New Tsukuba dataset. Experimental results show that the proposed method achieves better results for both speed and accuracy than RANSAC.

Binocular depth processing in the ventral visual pathway

One of the most powerful forms of depth perception capitalizes on the small relative displacements, or binocular disparities, in the images projected onto each eye. The brain employs these disparities to facilitate various computations, including sensori-motor transformations (reaching, grasping), scene segmentation and object recognition. In accordance with these different functions, disparity activates a large number of regions in the brain of both humans and monkeys. Here, we review how disparity processing evolves along different regions of the ventral visual pathway of macaques, emphasizing research based on both correlational and causal techniques. We will discuss the progression in the ventral pathway from a basic absolute disparity representation to a more complex three-dimensional shape code. We will show that, in the course of this evolution, the underlying neuronal activity becomes progressively more bound to the global perceptual experience. We argue that these observations most probably extend beyond disparity processing per se, and pertain to object processing in the ventral pathway in general. We conclude by posing some important unresolved questions whose answers may significantly advance the field, and broaden its scope.This article is part of the themed issue 'Vision in our three-dimensional world'.

Development of a Stereovision-Based Technique to Measure the Spread Patterns of Granular Fertilizer Spreaders

Centrifugal fertilizer spreaders are by far the most commonly used granular fertilizer spreader type in Europe. Their spread pattern however is error-prone, potentially leading to an undesired distribution of particles in the field and losses out of the field, which is often caused by poor calibration of the spreader for the specific fertilizer used. Due to the large environmental impact of fertilizer use, it is important to optimize the spreading process and minimize these errors. Spreader calibrations can be performed by using collection trays to determine the (field) spread pattern, but this is very time-consuming and expensive for the farmer and hence not common practice. Therefore, we developed an innovative multi-camera system to predict the spread pattern in a fast and accurate way, independent of the spreader configuration. Using high-speed stereovision, ejection parameters of particles leaving the spreader vanes were determined relative to a coordinate system associated with the spreader. The landing positions and subsequent spread patterns were determined using a ballistic model incorporating the effect of tractor motion and wind. Experiments were conducted with a commercial spreader and showed a high repeatability. The results were transformed to one spatial dimension to enable comparison with transverse spread patterns determined in the field and showed similar results.

Tracking a Non-Cooperative Target Using Real-Time Stereovision-Based Control: An Experimental Study

Tracking a non-cooperative target is a challenge, because in unfamiliar environments most targets are unknown and unspecified. Stereovision is suited to deal with this issue, because it allows to passively scan large areas and estimate the relative position, velocity and shape of objects. This research is an experimental effort aimed at developing, implementing and evaluating a real-time non-cooperative target tracking methods using stereovision measurements only. A computer-vision feature detection and matching algorithm was developed in order to identify and locate the target in the captured images. Three different filters were designed for estimating the relative position and velocity, and their performance was compared. A line-of-sight control algorithm was used for the purpose of keeping the target within the field-of-view. Extensive analytical and numerical investigations were conducted on the multi-view stereo projection equations and their solutions, which were used to initialize the different filters. This research shows, using an experimental and numerical evaluation, the benefits of using the unscented Kalman filter and the total least squares technique in the stereovision-based tracking problem. These findings offer a general and more accurate method for solving the static and dynamic stereovision triangulation problems and the concomitant line-of-sight control.

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera’s 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg–Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade–Lucas–Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.

Estimating 3D Leaf and Stem Shape of Nursery Paprika Plants by a Novel Multi-Camera Photography System

For plant breeding and growth monitoring, accurate measurements of plant structure parameters are very crucial. We have, therefore, developed a high efficiency Multi-Camera Photography (MCP) system combining Multi-View Stereovision (MVS) with the Structure from Motion (SfM) algorithm. In this paper, we measured six variables of nursery paprika plants and investigated the accuracy of 3D models reconstructed from photos taken by four lens types at four different positions. The results demonstrated that error between the estimated and measured values was small, and the root-mean-square errors (RMSE) for leaf width/length and stem height/diameter were 1.65 mm (R² = 0.98) and 0.57 mm (R² = 0.99), respectively. The accuracies of the 3D model reconstruction of leaf and stem by a 28-mm lens at the first and third camera positions were the highest, and the number of reconstructed fine-scale 3D model shape surfaces of leaf and stem is the most. The results confirmed the practicability of our new method for the reconstruction of fine-scale plant model and accurate estimation of the plant parameters. They also displayed that our system is a good system for capturing high-resolution 3D images of nursery plants with high efficiency.

An Evaluation of the Pedestrian Classification in a Multi-Domain Multi-Modality Setup

The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains. The experiments show that features families, intensity self-similarity (ISS), local binary patterns (LBP), local gradient patterns (LGP) and histogram of oriented gradients (HOG), computed from FIR and visible domains are highly complementary, but their relative performance varies across different modalities. In our experiments, the FIR domain has proven superior to the visible one for the task of pedestrian classification, but the overall best results are obtained by a multi-domain multi-modality multi-feature fusion.

On the use of orientation filters for 3D reconstruction in event-driven stereo vision

The recently developed Dynamic Vision Sensors (DVS) sense visual information asynchronously and code it into trains of events with sub-micro second temporal resolution. This high temporal precision makes the output of these sensors especially suited for dynamic 3D visual reconstruction, by matching corresponding events generated by two different sensors in a stereo setup. This paper explores the use of Gabor filters to extract information about the orientation of the object edges that produce the events, therefore increasing the number of constraints applied to the matching algorithm. This strategy provides more reliably matched pairs of events, improving the final 3D reconstruction.

Enhancing positioning accuracy in urban terrain by fusing data from a GPS receiver, inertial sensors, stereo-camera and digital maps for pedestrian navigation

The paper presents an algorithm for estimating a pedestrian location in an urban environment. The algorithm is based on the particle filter and uses different data sources: a GPS receiver, inertial sensors, probability maps and a stereo camera. Inertial sensors are used to estimate a relative displacement of a pedestrian. A gyroscope estimates a change in the heading direction. An accelerometer is used to count a pedestrian's steps and their lengths. The so-called probability maps help to limit GPS inaccuracy by imposing constraints on pedestrian kinematics, e.g., it is assumed that a pedestrian cannot cross buildings, fences etc. This limits position inaccuracy to ca. 10 m. Incorporation of depth estimates derived from a stereo camera that are compared to the 3D model of an environment has enabled further reduction of positioning errors. As a result, for 90% of the time, the algorithm is able to estimate a pedestrian location with an error smaller than 2 m, compared to an error of 6.5 m for a navigation based solely on GPS.

Parametric dense stereovision implementation on a system-on chip (SoC)

This paper proposes a novel hardware implementation of a dense recovery of stereovision 3D measurements. Traditionally 3D stereo systems have imposed the maximum number of stereo correspondences, introducing a large restriction on artificial vision algorithms. The proposed system-on-chip (SoC) provides great performance and efficiency, with a scalable architecture available for many different situations, addressing real time processing of stereo image flow. Using double buffering techniques properly combined with pipelined processing, the use of reconfigurable hardware achieves a parametrisable SoC which gives the designer the opportunity to decide its right dimension and features. The proposed architecture does not need any external memory because the processing is done as image flow arrives. Our SoC provides 3D data directly without the storage of whole stereo images. Our goal is to obtain high processing speed while maintaining the accuracy of 3D data using minimum resources. Configurable parameters may be controlled by later/parallel stages of the vision algorithm executed on an embedded processor. Considering hardware FPGA clock of 100 MHz, image flows up to 50 frames per second (fps) of dense stereo maps of more than 30,000 depth points could be obtained considering 2 Mpix images, with a minimum initial latency. The implementation of computer vision algorithms on reconfigurable hardware, explicitly low level processing, opens up the prospect of its use in autonomous systems, and they can act as a coprocessor to reconstruct 3D images with high density information in real time.

Hierarchical processing of horizontal disparity information in the visual forebrain of behaving owls

According to their restricted receptive fields and input-filter characteristics, disparity-sensitive neurons at early processing levels of the visual system perform rather ambiguous computations; they respond vigorously to disparity in false-matched images and show multiple response peaks in their disparity-tuning profiles. On the other hand, the perception of depth from binocular disparity is reliable, thus raising the question as to where and how in the brain additional processing is accomplished leading toward behaviorally relevant disparity detection. To address this issue, tuning data during stimulation with correlated and anticorrelated random-dot stereograms (a-RDS) were obtained from 52 disparity-sensitive visual Wulst neurons in three behaving owls. From the disparity-tuning curves, several quantitative measures were derived that allowed to determine the response ambiguity of a cell. A systematic decline of response ambiguities with increasing response latencies was observed. An increase in response latencies of neurons was correlated with a decrease of the strength of responses to a-RDS. Declining responses to a-RDS are expected for global detectors, because an owl was not able to discriminate depth in psychophysical tests with a-RDS. In addition, suppression of response side peaks was increased and disparity tuning was enhanced with growing response latencies. These results suggest a functional hierarchy of disparity processing in the owl's forebrain, leading from spatial filters to more global disparity detectors that may be able to solve the correspondence problem. Nonlinear threshold operations and inhibition are proposed as candidate mechanisms to resolve coding ambiguities.