Visual Research Articles

LIVS: a tightly coupled LiDAR, IMU, and camera-based SLAM system under scene degradation

In increasingly complex environments, single-sensor-based SLAM systems face scene degradation problems such as strong light, dynamic obstacle interference, and lack of structural features in the environment, which severely constrain the localization accuracy and mapping effectiveness of SLAM systems. To address this problem, this paper proposes a tightly coupled laser-IMU-visual SLAM system (LIVS) based on factor graph optimization. LIVS consists of two subsystems: the laser inertial system (LIS) and the visual inertial system (VIS). The pose estimation of the LIS can provide an initialization for the VIS; LiDAR suffers scene degradation in environments lacking structural features, while the VIS provides better constraints for Lidar in this environment. Firstly, a method of selecting keyframes based on ORB features and the relative motion of the mobile robot is proposed as a means of improving the positioning accuracy and tracking ability of the system in the case of strenuous motion, and a strategy of local sliding window optimization is adopted to effectively improve the real-time performance and robustness of the system. Meanwhile, in order to further improve the global map consistency and positioning accuracy, a hybrid closed-loop detection method based on laser and vision is proposed, which utilizes the geometrical features of laser and the image features of vision to accomplish the hybrid closed-loop detection. Secondly, the laser inertia factor, IMU pre-integration factor, vision inertia factor, and closed-loop factor are globally optimized in a factor map framework to achieve accurate estimation of the robot pose. Finally, this paper presents experimental evaluations on both public and homemade datasets and compares the performance of the proposed algorithm with that of other algorithms. Experimental results show that the algorithm in this paper exhibits better performance in both localization accuracy and mapping effectiveness.

Visualization Analysis of Integrating College Sports Training and Psychology into Basketball Physical Education Teaching System Based on Image Recognition Algorithm

ABSTRACT On this basis, a basketball movement model based on ORB (Oriented FAST and Rotated BRIEF) local feature extraction has been proposed, and a basketball teaching visualization analysis system has been constructed. By extracting images from athletes’ videos in basketball, and using their training as a standard, tracking the frequency of their various celebration postures appearing and improving their scores in the game, corresponding feature points are extracted, and then the BP (back propagation) neural network algorithm is used to classify feature points. Ten different participants were selected from 10 games. Their movements were tracked, and then the extracted feature actions were imported into the visualization system for visual analysis, comparing the changes before and after psychological intervention. The results showed that there were significant differences in scores, errors, hit rates, steals, and motivation among subjects who received psychological cues and incentives compared to the data before psychological counseling. The scores and positive and negative values increased to 2–4 points, which had a certain positive impact on the competitive results.

المعنى المشترك وجماليات الخطاب في التصميم الداخلي

Designers seek to create a design product that is dialogic and communicative with the largest number of segments of society, with visual formations that prepare for a spatial environment that is distinguished by intellectual richness and seeks to communicate with minds. Then, the design represents a visual discourse that influences the recipient, as an intentional message that reaches his imagination with its idea, including the aesthetic meanings inherent in it, and what its intellectual and semantic content carries, the aim of which is to reach a common meaning between the designer and the recipient so that the designer can lead the recipient's behavior according to the ideas presented by the design. Therefore, the research problem was formulated with the following question: "Is interior design concerned with visual formations to highlight formal values that aim to improve the aesthetic taste through the visual reception system of the recipient only, or is it an ideology that indicates that these formations are more than just what the eye sees because of their connection to the shared latent meaning between the designer and the recipient, which is reflected in the nature of collective behavior?" The research aimed to "reveal the data of the aesthetic image of the formal discourse by translating the latter into an internal space that gives the recipient interpretations that are in harmony with what the designer is going for as a directed message with intent and meaning." The research came out with a set of conclusions, the most important of which are: The design product constitutes a message with a clear meaning when it is a reflection of the social, cultural, material and geographical environment of the design context through the aesthetic formations of the design discourse, and that the reception mechanism is not destined to succeed unless the designer has a specific idea that reflects the privacy of society and the identity of the place through what the design broadcasts in order to obtain a clear and easy response from the recipient and decipher the symbols of the discourse and enjoy its connotations and goals.

New Solution to 3D Projection in Human-like Binocular Vision

A human eye has about 120 million rod cells and 6 million cone cells. This huge number of light-sensing cells inside a human eye will continuously produce a huge quantity of visual signals that flow into the human brain for daily processing. However, the real-time processing of these visual signals does not cause excessive energy consumption by the human brain. This fact tells us the truth which is to say that human-like vision processes do not rely on complicated and expensive formulas to compute depth, displacement, and colors. On the other hand, the human eye is like a camera with pan-tilt (PT) motions. We all know that in computer vision, each set of PT parameters (i.e., coefficients of pan motion as well as tilt motion) requires a dedicated calibration to determine a camera’s projection matrix. Since there is an infinite number of PT parameters that could be produced by a human eye, it is unlikely that a human brain stores an infinite number of calibration matrices for each human eye. These observations inspire us to look for a simpler and computationally non-expensive solution which is to undertake three-dimensional (3D) projection in human-like binocular vision. In other words, it is an interesting question for us to answer, which is to say whether simpler and learning-friendly formulas for computing depth and displacement exist or not. If the answer is yes, these formulas must also be calibration-friendly (i.e., easy process on the fly or on the go). In this paper, we present an important discovery of a new solution to 3D projection in a human-like binocular vision system. This solution is computationally simpler and could be easily learned or calibrated on the fly. We know that the purpose of doing 3D projection in binocular vision is to undertake forward and inverse transformations (or mappings) between coordinates in 2D digital images and coordinates in a 3D analogue scene. The formulas underlying the new solution are accurate, easily computable, easily tunable (i.e., to be calibrated on the fly or on the go) and could be easily implemented by a neural system (i.e., a network of neurons or a network of computational flows). Experimental results have validated the newly derived formulas which are better than textbook solutions.

Border-ownership tuning determines the connectivity between V4 and V1 in the macaque visual system

Cortical feedback connections are extremely numerous but the logic of connectivity between higher and lower areas remains poorly understood. Feedback from higher visual areas to primary visual cortex (V1) has been shown to enhance responses on perceptual figures compared to backgrounds, an effect known as figure-background modulation (FBM). A likely source of this feedback are border-ownership (BO) selective cells in mid-tier visual areas (e.g. V4) which represent the location of figures. We examined the connectivity between V4 cells and V1 cells using noise-correlations and micro-stimulation to estimate connectivity strength. We show that connectivity is consistent with a model in which BO-tuned V4 cells send positive feedback in the direction of their preferred figure and negative feedback in the opposite direction. This connectivity scheme can recreate patterns of FBM observed in previous studies. These results provide insights into the cortical connectivity underlying figure-background perception and establish a link between FBM and BO-tuning.

Why I Paint Thousands of Circles

Why I paint Thousands of Circles explores psychological barriers and multilayered themes that stem from a single horrific event that involved Moran’s father and his brother. The artist collates information, photos and constructs an ar(t)chaeological archive where family photos, product imagery, together with newspaper clips to form units of a historical and psychological mind map. The exposition becomes an auto-ethnographical exploration of mid 90's working class North West London. The repetitive painting process, exposed and documented in the exposition, functions as transformative method, where ambiguous feelings of a violent upbringing are directed towards the creation of a visual system with an inherent logic – “creating some kind of beauty out of ugliness.”

A Computationally Efficient Neuronal Model for Collision Detection with Contrast Polarity-Specific Feed-Forward Inhibition

Animals utilize their well-evolved dynamic vision systems to perceive and evade collision threats. Driven by biological research, bio-inspired models based on lobula giant movement detectors (LGMDs) address certain gaps in constructing artificial collision-detecting vision systems with robust selectivity, offering reliable, low-cost, and miniaturized collision sensors across various scenes. Recent progress in neuroscience has revealed the energetic advantages of dendritic arrangements presynaptic to the LGMDs, which receive contrast polarity-specific signals on separate dendritic fields. Specifically, feed-forward inhibitory inputs arise from parallel ON/OFF pathways interacting with excitation. However, none of the previous research has investigated the evolution of a computational LGMD model with feed-forward inhibition (FFI) separated by opposite polarity. This study fills this vacancy by presenting an optimized neuronal model where FFI is divided into ON/OFF channels, each with distinct synaptic connections. To align with the energy efficiency of biological systems, we introduce an activation function associated with neural computation of FFI and interactions between local excitation and lateral inhibition within ON/OFF channels, ignoring non-active signal processing. This approach significantly improves the time efficiency of the LGMD model, focusing only on substantial luminance changes in image streams. The proposed neuronal model not only accelerates visual processing in relatively stationary scenes but also maintains robust selectivity to ON/OFF-contrast looming stimuli. Additionally, it can suppress translational motion to a moderate extent. Comparative testing with state-of-the-art based on ON/OFF channels was conducted systematically using a range of visual stimuli, including indoor structured and complex outdoor scenes. The results demonstrated significant time savings in silico while retaining original collision selectivity. Furthermore, the optimized model was implemented in the embedded vision system of a micro-mobile robot, achieving the highest success ratio of collision avoidance at 97.51% while nearly halving the processing time compared with previous models. This highlights a robust and parsimonious collision-sensing mode that effectively addresses real-world challenges.

Retinal Ganglion Cell Subtypes and Their Vulnerability in Glaucoma.

The detection of selective retinal ganglion cell damage in glaucoma has been a long sought-after goal, not just for the development of clinical tests for the early detection of glaucoma but for the elucidation of potential mechanisms underlying retinal ganglion cell loss. Early reports of the selective vulnerability of larger retinal ganglion cells (RGCs) in human studies did not translate simply to the loss of a particular class of RGC but more likely reflected shrinkage and degeneration across all RGC classes. Subsequent studies of nonhuman primate (NHP) models of glaucoma indicated some selectivity with great damage to the magnocellular vs parvocellular pathways. More recently, rodent models of experimental glaucoma have highlighted a selective vulnerability of OFF-centered RGCs-particularly those with transient responses. Selectivity for OFF pathway damage is also seen as a trend in a rat model of glaucoma. These data support the concept that some RGCs are more vulnerable to the effects of glaucoma damage. This chapter covers some of the methods to elucidate RGC damage and the relevance of model selection to mimic human glaucoma rather than just RGC death.

Achromatic solutions of the color constancy problem: the Helmholtz–Kohlrausch effect explained

For given tristimulus values X, Y, Z of the object with reflectance ρ(λ) viewed under an illuminant S(λ) with tristimulus values X0, Y0, Z0, an earlier algorithm constructs the smoothest metameric estimate ρ0(λ) under S(λ) of ρ(λ), independent of the amplitude of S(λ). It satisfies a physical property of ρ(λ), i.e., 0≤ρ0(λ)≤1, on the visual range. The second inequality secures the condition that for no λ the corresponding patch returns more radiation from S(λ) than is incident on it at λ, i.e., ρ0(λ) is a fundamental metameric estimate; ρ0(λ) and ρ(λ) differ by an estimation error causing perceptual variables assigned to ρ0(λ) and ρ(λ) under S(λ) to differ under the universal reference illuminant E(λ)=1 for all λ, tristimulus values X E , Y E , Z E . This color constancy error is suppressed but not nullified by three narrowest nonnegative achromatic response functions A i (λ) defined in this paper, replacing the cone sensitivities and invariant under any nonsingular transformation T of the color matching functions, a demand from theoretical physics. They coincide with three functions numerically constructed by Yule apart from an error corrected here. S(λ) unknown to the visual system as a function of λ is replaced by its nonnegative smoothest metameric estimate S0(λ) with tristimulus values made available in color rendering calculations, by specular reflection, or determined by any educated guess; ρ(λ) under S(λ) is replaced by its corresponding color R0(λ) under S0(λ) like ρ(λ) independent of the amplitude of S0(λ). The visual system attributes to R0(λ)E(λ) one achromatic variable, in the CIE case defined by y(λ)/Y E , replaced by the narrowest middle wave function A2(λ) normalized such that the integral of A2(λ)E(λ) over the visual range equals unity. It defines the achromatic variable ξ2, A(λ), and ξ as described in the paper. The associated definition of present luminance explains the Helmholtz–Kohlrausch effect in the last figure of the paper and rejects CIE 1924 luminance that fails to do so. It can be understood without the mathematical details.

Visual coding along multiple brain areas

This study focuses on understanding visual coding in multiple brain areas and its implications for neural processing in the visual system. It highlights the use of simultaneous recordings of large neuronal populations to investigate how visual information is encoded and processed in the brain. By studying the activity of multiple brain areas, the paper aims to uncover the mechanisms underlying brain-wide visual perception and provide insights into the neural basis of visual processing. The findings of this research contribute to the broader field of neuroscience and have implications for understanding visual disorders and developing therapeutic interventions

High-Precision Disparity Estimation for Lunar Scene Using Optimized Census Transform and Superpixel Refinement

High-precision lunar scene 3D data are essential for lunar exploration and the construction of scientific research stations. Currently, most existing data from orbital imagery offers resolutions up to 0.5–2 m, which is inadequate for tasks requiring centimeter-level precision. To overcome this, our research focuses on using in situ stereo vision systems for finer 3D reconstructions directly from the lunar surface. However, the scarcity and homogeneity of available lunar surface stereo datasets, combined with the Moon’s unique conditions—such as variable lighting from low albedo, sparse surface textures, and extensive shadow occlusions—pose significant challenges to the effectiveness of traditional stereo matching techniques. To address the dataset gap, we propose a method using Unreal Engine 4 (UE4) for high-fidelity physical simulation of lunar surface scenes, generating high-resolution images under realistic and challenging conditions. Additionally, we propose an optimized cost calculation method based on Census transform and color intensity fusion, along with a multi-level super-pixel disparity optimization, to improve matching accuracy under harsh lunar conditions. Experimental results demonstrate that the proposed method exhibits exceptional robustness and accuracy in our soon-to-be-released multi-scene lunar dataset, effectively addressing issues related to special lighting conditions, weak textures, and shadow occlusion, ultimately enhancing disparity estimation accuracy.

Persistent Craniopharyngeal Canal (Type 3C) with Vertebrobasilar Dolichoectasia and Bilateral Sclerochoroidal Calcification

AbstractThe persistent craniopharyngeal canal is a rare, well-corticated midline congenital bony defect through the sphenoid bone between the sellar floor and the nasopharyngeal roof. The prevalence of persistent craniopharyngeal canal is reported to be 0.42%. A 42-year-old male was evaluated for nasal discharge and progressive vision loss; and underwent computed tomography and magnetic resonance imaging, which revealed a large craniopharyngeal canal with ectopic pituitary, lipoma, encephalocele, deformed globe with sclerochoroidal calcification and vertebrobasilar dolichoectasia. The presence of orbital and optic tract malformation, craniofacial anomalies, and tumors can be associated with the craniopharyngeal canal.

Insights from the Evolving Model of Two Cortical Visual Pathways.

The two cortical visual pathways framework has had a profound influence on theories and empirical studies of the visual system for over 40 years. By grounding physiological responses and behavior in neuroanatomy, the framework provided a critical guide for understanding vision. Although the framework has evolved over time, as our understanding of the physiology and neuroanatomy expanded, cortical visual processing is still often conceptualized as two separate pathways emerging from the primary visual cortex that support distinct behaviors ("what" vs. "where/how"). Here, we take a historical perspective and review the continuing evolution of the framework, discussing key and often overlooked insights. Rather than a functional and neuroanatomical bifurcation into two independent serial, hierarchical pathways, the current evidence points to two highly recurrent heterarchies with heterogeneous connections to cortical regions and subcortical structures that flexibly support a wide variety of behaviors. Although many of the simplifying assumptions of the framework are belied by the evidence gathered since its initial proposal, the core insight of grounding function and behavior in neuroanatomy remains fundamental. Given this perspective, we highlight critical open questions and the need for a better understanding of neuroanatomy, particularly in the human.

Intelligent Monitoring and Visualization System for High Building Nighttime Utilization Based on Image Processing.

The rise of complex high-rise buildings has made building management increasingly challenging, especially the nighttime supervision of university laboratories. Idle occupation increases the risk of accidents and undermines campus sustainability. Effective occupancy detection is essential for optimizing campus building safety and energy efficiency. Environmental sensors for occupancy detection offer limited coverage and are costly, making them unsuitable for campuses. Surveillance cameras, as part of campus infrastructure, provide wide coverage. On this basis, we designed a detection algorithm that uses light brightness to assess nighttime building use. Experimental results showed that the algorithm achieves an average accuracy of 98.67%, enabling large-scale nighttime occupancy detection without the need for installing additional sensors, significantly improving the efficiency of campus building management. In addition, to address the limitations of indoor space representation in geographic information system (GIS) management models, this paper developed a comprehensive 3D GIS model based on a "building-floor-room" hierarchical structure, utilizing oblique photogrammetry and laser scanning technology. This study combined the detection results with real-world 3D data for visualization, providing a new perspective for the 3D spatiotemporal refinement of complex high-rise buildings, and providing a reference framework for the detection and analysis of other types of building environments.

Visual short-term memory for crossed and uncrossed binocular disparities.

Previous work on visual short-term memory (VSTM) has encompassed various stimulus attributes including spatial frequency, color, and contrast, revealing specific time courses and a dependence on stimulus parameters. This study investigates visual short-term memory for binocular depth, using dynamic random dot stereograms (DRDS) featuring disparity planes in front of or behind the plane of fixation. In a delayed match-to-sample paradigm, we employed four distinct reference disparities (17.5', 28.8' either crossed or uncrossed) at two contrast levels (20%, 80%), spanning interstimulus intervals (ISI) of up to 4 s. Test stimuli represented a range of equally spaced values centered around the reference disparity of the ongoing trial. In addition, the impact of a memory masking stimulus was also tested in a separate experiment. Accuracy and point of subjective equality (PSE) served as performance markers. The performance, indicated by the accuracy of responses, was better for smaller reference disparities (±17.5') compared to larger ones (±28'), but both deteriorated as a function of ISI. The PSE demonstrated a consistent shift with increasing ISIs, irrespective of the magnitude of the initial disparity, converging gradually toward the range of 20-22' and deviating from the reference disparity. Notably, the influence of masking stimuli on the PSE was more marked when the mask disparity diverged from the reference value. The findings from our study indicate that the retention of absolute disparity in memory is imprecise, it deteriorates with retention time or due to perturbation by dissimilar masking stimuli. As a result, the memory trace is gradually replaced by a default depth value. This value could potentially signify an optimal point within low-level perceptual memory, however, our results are better explained by perceptual averaging whereby the visual system computationally derives a statistical summary of the presented disparities over time. The latter mechanism would aid in the computation of relative disparity in a dynamically changing environment.

Activity-dependent synapse clustering underlies eye-specific competition in the developing retinogeniculate system.

Co-active synaptic connections are often spatially clustered to facilitate local dendritic computations underlying learning, memory, and basic sensory processing. In the mammalian visual system, retinal ganglion cell (RGC) axons converge to form clustered synaptic inputs that enable local signal integration in the dorsal lateral geniculate nucleus (dLGN) of the thalamus. While visual experience promotes retinogeniculate synapse clustering after eye-opening, the earliest events in cluster formation prior to visual experience are unknown. Here, using volumetric super-resolution single-molecule localization microscopy and eye-specific labeling of developing retinogeniculate synapses in mice, we show that synaptic clustering is eye-specific and activity-dependent during retinogeniculate refinement in the first postnatal week. We identified a subset of retinogeniculate synapses with multiple active zones that are surrounded by like-eye synapses and depleted of synapse clustering from the opposite eye. In mutant mice with disrupted spontaneous retinal wave activity, synapses with multiple active zones still form, but do not exhibit the synaptic clustering seen in controls. These results highlight a role for spontaneous retinal activity in regulating eye-specific synaptic clustering in circuits essential for visual perception and behavior.

Understanding contrast perception in amblyopia: a psychophysical analysis of the ON and OFF visual pathways.

The study aimed to explore potential discrepancies in contrast sensitivity in the ON and OFF visual pathways among individuals with amblyopia compared to controls. Eleven adult amblyopes (26.2 ± 4.4 [SD] years old) and 10 controls (24.6 ± 0.8 years old) with normal or corrected to normal visual acuity (logMAR VA ≤ 0) participated in this study. Using the quick contrast sensitivity function (qCSF) algorithm, we measured balanced CSF which would stimulate the ON and OFF pathways unselectively, and CSFs for increments and decrements that would selectively stimulate the ON and OFF visual pathways. Contrast sensitivity and area under log contrast sensitivity function were extracted for statistical analysis. For the balanced CSF, we found significant interocular differences in sensitivity and area under log contrast sensitivity function in both amblyopes [F(1,10) = 74.992, p < 0.001] and controls [F(1,9) = 35.6, p < 0.001], while such differences were more pronounced in amblyopes than in controls. For increment and decrement CSFs, we found that the increment sensitivity (p = 0.038) and area under log contrast sensitivity function (p = 0.001) were significantly lower than the decrement in the amblyopic eye. Such differences between increment and decrement CSFs were not observed in the fellow eye of the amblyopes or in the controls. There is a subtle difference in the contrast sensitivity of the amblyopic eye when exposed to stimulation in the ON and OFF pathways.

OPTICAL BLUR AFFECTS DIFFERENTLY ON AND OFF VISUAL PATHWAYS.

Optical blur affects ON and OFF pathways differently.Blur expands ON but shrinks OFF receptive fields, weakening OFF more than ON signals.Magnification from positive blur reduces OFF more than ON signal strength and latency.ON-OFF response balance can signal retinal image quality and guide eye growth. Pons et al. demonstrate that optical blur affects differently the receptive field properties and responses from ON and OFF visual pathways, revealing a new relation between ON/OFF pathway balance and blurred visual perception. The results highlight a new role of ON and OFF pathways in optimizing retinal image quality that can have implications for the regulation of eye growth.

Deep learning reconstruction of diffusion-weighted brain MRI for evaluation of patients with acute neurologic symptoms

Purpose: We aimed to evaluate whether the deep-learning (DL) accelerated diffusion weighted image (DWI) is clinically feasible for evaluating patients with acute neurologic symptoms, regarding its shorter study time and acceptable image quality. Materials and methods: In this retrospective study, brain images obtained at DWI with a b-value of 0 s/mm2 and DWI with a b-value of 1000 s/mm2 (DWI 1000) from 321 consecutive patients with acute stroke-like symptom were reconstructed with and without DL algorithm. We compare the diagnostic performance between DL-DWI and conventional DWI for detecting brain lesions, including acute infarction. We assessed the diagnostic accuracy of conventional DWI and DL-DWI and compared the results. Qualitative analysis based on image quality was assessed and compared using a five-point visual scoring system. Apparent diffusion coefficients (ADCs) from DWI with and without DL were also compared. Results: The mean acquisition time for the DL-DWI (49 s) was significantly shorter (P < 0.001) than conventional DWI (165 s). Both DWI with and without DL showed similar performance in diagnosing brain lesions especially sensitivity (98.8% in both DWI and DL-DWI) and specificity (99.5% in both DWI and DL-DWI). Overall image quality, gray-white matter and deep gray matter differentiation of two sequences were similar. DL DWI showed more artifacts than DWI. Lesion conspicuity, especially smaller than 5 mm, was better with DL DWI than conventional DWI (p = 0.03). ADC values of white matter, deep gray matter, and pons with DL were lower than conventional DWI. Conclusions: Compared to conventional DWI, DL-DWI achieved comparable image quality and brain lesion visualization for acute neurological symptoms, with a significantly shorter scan time.

Retraction Note: Design of optical sensors based on computer vision in basketball visual simulation system

Retraction Note: Design of optical sensors based on computer vision in basketball visual simulation system