Distant Objects Research Articles

SEGANet: 3D object detection with shape-enhancement and geometry-aware network

3D object detection approaches from point clouds develop rapidly. However, the distribution of point clouds is unbalanced in the real scene, and thus the distant or occluded objects suffer from too few points to be perceived. This case damages the overall detection accuracy. Hence, we propose a novel two-stage 3D object detection framework, the Shape-Enhancement and Geometry-Aware Network (SEGANet), which aims to mitigate the negative impact of unbalanced point distribution for boosting detection performance. In stage 1, we first capture fine-grained structural knowledge with the assistance of point-wise features from voxels to generate proposals. And in stage 2, we construct a shape enhancement module to reconstruct complete surface points for objects within proposals, then establish an elaborate geometric relevance-aware Transformer module to aggregate high-correlated feature pairs of reconstructed-known parts and decode vital geometric relations of aggregated features. Thus, critical geometric clues are supplied for objects from the data and feature levels, achieving enhanced features for box refinement. Extensive experiments on KITTI and Waymo datasets show that SEGANet achieves low model complexity and excellent detection accuracy, especially leading the baseline method by 2.18% gain in overall detection accuracy and 1.8% gain in average accuracy of weakly sensing objects. This verifies that SEGANet effectively alleviates the impact of point imbalance to significantly boost detection performance.

Spatio-chromatic vision with multifocal diffractive intraocular lens

BackgroundThis study aims to detect alterations in the spatio-chromatic pseudophakic vision produced by multifocal diffractive intraocular lenses (IOLs) and provides a physical interpretation.MethodsIn vitro characterization of the imaging performance of two diffractive IOLs: AT LISA Tri (Zeiss) and FineVision (PhysIOL) in on-bench model eye illuminated with red (R, 625 nm), green (G, 530 nm) and blue (B, 455 nm) lights. We used the metrics: energy efficiency (EE), area under the modulation transfer function, longitudinal chromatic aberration (LCA), and halo intensity. Through-focus (TF) analysis and calculation of the expected defocus curve under white (W) daylight were included. In vivo visual acuity (VA) of 50 pseudophakics (60 eyes) was assessed under W, R, G, B lights at far and near. Two clinical experiments evaluated LCA and R, G, B TF-EE effects on pseudophakic vision and their relative importance.ResultsClinical mean VA values under W light agreed with the predicted values at far and near for both IOLs. LCA measurements and R, G, B TF-EE curves were consistent with their lens design based on the 0th and 1st diffraction orders operative for far and near vision, respectively. LCA effects were compensated at near but noticed at far (− 0.75 D under B light). We detected strong asymmetry in visual resolution depending on the object distance and the illuminating wavelength—red predominance at far, blue predominance at near—in consistency with the TF-EE measurements.ConclusionsDiffractive multifocal IOL designs produce asymmetries in the spatio-chromatic vision of pseudophakics beyond the alterations strictly due to LCA. VA asymmetry for far/near object distance under R and B illumination is clinically detectable in subjects implanted with IOLs with 0th and 1st diffraction orders for far and near vision, respectively. Such VA asymmetry cannot be explained solely from the influence of defocus, as would be derived from a chromatic difference of power, but mainly from the wavelength dependence of the EE.

Safe Distance Monitoring of Live Equipment Based Upon Instance Segmentation and Pseudo-LiDAR

Electrocution accidents caused by operation and maintenance personnel and high-voltage live equipment frequently occur in substations. Although many cameras have been installed for the surveillance of critical energized equipment, they cannot complete the monitoring of safe distance. In addition, the current research based on vision or LiDAR suffers from computationally intensive, lack of real-time or expensive equipment. In order to meet the low cost, easy maintenance and real-time requirements of substation safe distance monitoring, a monocular vision method based on 2D-3D fusion is proposed in this study. Specifically, instance segmentation, depth estimation, depth reconstruction, and back projection transformation are used to predict the 3D distance of objects in 2D images. The work is mainly implemented in two aspects: a) To obtain the high-quality masks of Power Transformers and Person, SOLOv2 is optimized on three aspects: feature extraction, feature fusion and ability to cope with object geometric transformation. b) Pseudo-LiDAR output from RGB images via depth estimation and back projection techniques. Subsequently, combined with the point cloud of the object and the actual-to-virtual conversion ratio, the actual distance between Power Transformer and Person can be calculated. Experimental results show that the maximum error of ranging is within 9%, with an average error rate of 5.34% on the Power Transformer-Person dataset. It can be seen that the proposed method has achieved good ranging effects, and can realize the automatic measurement of the safe distance of Power Transformer.

Experimenting on semiconductors using ablative laser propulsion to investigate propulsion parameters

A laser can be used to propel distant objects. The ability of silicon to produce thrust and its propulsive parameters are needed to be studied in ablative laser propulsion (ALP). In this work, pure silicon and silicon doped with indium were subjected to ALP to achieve the momentum coupling coefficient and specific impulse to investigate its worth as a propellant. The experiment was conducted using the Nd:YAG laser (Quantel Brilliant) operating at fundamental harmonic (λ = 1064 nm and 5 ns pulse duration). In the given range of fluence, 1 × 105–5 × 105 J/m2, no significant difference among both samples for values of momentum coupling coefficient (Cm) and specific impulse (Isp) is observed; for instance, both propellants follow a decreasing trend for Cm. However, maximum enhancement for Cm and Isp is observed with a cavity aspect ratio of one. Cm and Isp are enhanced about 1.75 and 4.5 times, respectively, for pure silicon. The external cavity does not have any impact on Cm values for indium-doped silicon while values of Isp showed considerable enhancement.

Visual Performance After Unilateral Implantation of an Extended Depth-of-Focus Intraocular Lens in Patients With Unilateral Cataract.

To investigate the visual performance after unilateral implantation of an extended depth-of-focus intraocular lens (IOL) in patients with unilateral cataracts. In this prospective study, uneventful phacoemulsification with LuxSmart IOL (Bausch & Lomb) implantation was performed in 25 eyes of 25 patients with unilateral cataracts. At postoperative 1, 4, 12, and 24 weeks, uncorrected and corrected visual acuity at far, intermediate, and near distances and the spherical equivalent in manifest refraction were measured. A Visual Function Index and modified Visual Function Index questionnaire were used to investigate glare, spectacle dependence, and satisfaction at 24 weeks in the eye that had surgery. At 6 months postoperatively, uncorrected distance visual acuity was 20/20 (0.0 logMAR) in 96% of cases, distance corrected intermediate visual acuity was 20/32 (0.2 logMAR) in all cases (60 cm), and distance corrected near visual acuity was 20/32 (0.2 logMAR) in 60% of cases (40 cm). The patient satisfaction score was 100% based on the Visual Function Index questionnaire for far and intermediate distance, respectively. No patients complained of the permanent photic phenomenon. No patients reported bilateral imbalance. All of the patients became spectacle independent for most of their intermediate activities at 60 cm. A total of 96% of the patients reported 100% contrast sensitivity in the Pelli-Robson test. The unilateral implantation of this EDOF IOL seems to be tolerated and effective in improving the visual function of patients with unilateral cataract with limited optical side effects such as halos or glare, providing spectacle-independent vision from far to intermediate object distances. [J Refract Surg. 2023;39(8):518-523.].

Cross-domain video action recognition via adaptive gradual learning

Video-based Unsupervised Domain Adaptation (UDA) methods concentrate on addressing domain shift and improving the robustness of video models. It can be naturally applied to cross-domain action recognition tasks, but the inherent complexity of videos makes this task more challenging. Though several recent attempts have achieved superior performance in the video UDA field, most of them intend to mitigate domain shift directly from the source domain to the target domain. These methods will cause a performance drop when the domain distribution shift is large. To better realize the domain adaptation, this paper proposes an effective gradual learning framework by constructing multiple auxiliary domains to achieve progressive transfer for cross-domain video action recognition. Specifically, a Dynamic CutMix Mechanism (DCM) is introduced to build the auxiliary domains that mitigate the domain gap caused by object distance and background discrepancies. Furthermore, the Gradual Transfer Strategy (GTS) utilizes these auxiliary domains to realize the cross-domain action classification gradually. Extensive experiments validate the effectiveness of our proposed method, and the experimental results can significantly outperform state-of-the-art methods on multiple benchmark cross-domain datasets.

Smart Doors For Monitoring Body Temperature And Space Capacity Based On IoT

Presently, multiple countries are engaged in combatting virus outbreaks transmitted through contact with infected individuals. To address this issue, several measures have been taken to shift the pandemic status to an endemic state. This study introduces an Internet of Things (IoT) device designed to monitor body temperature and room occupancy in real-time. Notifications are sent when a room surpasses its capacity or when body temperature exceeds the allowable threshold. The system enables real-time alerts and stores data for remote accessibility and analysis. The experiments conducted involve Infra Red Proximity, temperature sensor (MLX90614), object distance sensor (HCSR04), Wemos, and Solenoid Door Lock. Telegram is used as the medium for data transmission. The developed system proves effective in continuously monitoring body temperature and room occupancy.

Ayurvedic management of Keratoconus - A Case Report

This study reports a case of 37 years old female who had presented with the complaints of blurred vision in left eye for distant objects and also frequent headache and photophobia on exposure to bright light with heaviness in both of the eyes. The subject approached us with the reports of already performed corneal topography where corneal ectasia could be appreciated in both the eyes. The subject was already diagnosed as Keratoconus at previous hospital where she had consulted before. Ayurvedic treatment was initiated with Basti, Nasya, local ocular therapeutics which included Pindi, Bidalaka, Netra Prakshalana and Tarpana. The subject reported reduction in symptoms within 3 months of the treatment. It was observed that there was no progression of the disease from the findings of corneal topography which was repeated after the treatment within 3 months of initial visit.

How Camera-to-Subject Distance and Height Affect Breast Measurement and Follow-Up Assessment in Plastic Surgery.

Due to several factors that affect photograph quality, bias is inevitably present in two-dimensional (2D) breast photography. The principal variables affecting image performance at a fixed focus length are the distance between the camera and the subjects and the photography angles. This study aimed to investigate the effects of camera-to-subject distances and camera height on breast measurement parameters to understand the trend of breast deformation and provide guidance for the accurate evaluation of planar follow-up. We enlisted 16 volunteers with various breast cup sizes (A-D). Frontal and lateral photos were obtained with a steady focus of 50 mm at distances between 1.10 m and 2.20 m and at heights between 30 cm above the nipple and 30 cm below the nipple at intervals of 10 cm. Two researchers independently evaluated each volunteer's breast aesthetic parameters, including 11 linear parameters, 3 area parameters, and 3 ratio parameters, using Vernier calipers and Photoshop. The correlation coefficient of the two investigators ranged from 0.922 to 0.999. The results measured by Photoshop were 29.67 ± 5.23% greater than those of the Vernier caliper (p < 0.01). In contrast to ratio parameters, which showed no significant changes in each distance group (p = 1.00), linear parameters and area parameters significantly increased as object distance decreased (p < 0.05). The lower pole of the breast grew wider and flatter and occupied a larger proportion of the breast as height declined. Camera-to-subject distances of 1.5-1.7 m are recommended for stabilized and uniform breast photography. Varying shooting height affects breast distortion. Quantifying the relationship between photographic conditions and breast morphology enables plastic surgeons to conduct more comprehensive and accurate assessments. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266. Bullet point list: 1. The breast morphology will get more distortion with a smaller camera-to-subject distance. 2. Camera-to-subject distances of 1.5~1.7m are recommended for stabilized and uniform breast photography. 3. Height rather than distance affects the breast proportion.

Photocontrollable Elongation Actuation of Liquid Crystal Elastomer Films with Well-Defined Crease Structures.

Although liquid crystal elastomers (LCEs) have demonstrated various applications in artificial muscles and soft robotics, their inherent flexibility and orientation-dependent forces limit their functions. For instance, LCEs can sustain a high actuation force when they contract but cannot elongate to drive loads with large displacements. In this study, it is demonstrated that photocontrollable elongation actuation with a large strain can be achieved in polydomain LCEs by programming the crease structures in a well-defined order to couple the actuation forces. Efficient photoactuation without overheating-induced damage to the materials is favored, based on the well-designed photosensitive molecular switch crosslinker via the synergy of photochemical and photothermal effects. The LCE actuator can jack up heavy loads, elongate freely, and contract back to manipulate distant objects. Theoretical analysis based on a finite element simulation of the deformation energy during the actuation process reveals a trade-off between the abilities of jacking-up and withstanding load. More importantly, this study simplifies the design of a single material with functions inherent only in other soft robotic devices based on the assembly of multiplemodules, thus providing a design strategy for surpassing instinctive properties of conventional soft materials to expand the functions of soft robotics.

Quantifying Egocentric Distance Perception in Virtual Reality Environment

In virtual reality (VR) studies, where object distance plays a role of an independent variable, unknown egocentric distance perception values can affect the interpretation of the collected data. It is known that the perceived egocentric distance in VR is often underestimated, which may affect other judgments that implicitly depend on it. In order to prepare later experiments on the effect of distance on audiovisual (a)synchrony perception, this study quantifies the egocentric distance perception in a virtual indoor environment using two methods: verbal judgment (VJ) and position adjustment (PA). For the VJ method, participants verbally estimated the distance between their own position and a cardboard box position at a distance between a nominal 5 m and 30 m, with increments of 5 m. For the PA method, participants were asked to position a cardboard box to an instructed distance of a nominal 5 m to 13 m, with increments of 1 m. Both methods (VJ and PA) showed significant and substantial levels of underestimation, where simulated distance was underestimated on average by 38.5%. Our study suggests taking these findings into account when treating distance as an independent parameter in experiments conducted in purely simulated virtual spaces which do not exist physically in the real world.

Interplanetary scintillation observation and space weather modelling

Interplanetary scintillation (IPS) refers to random fluctuations in radio intensity of distant small-diameter celestial object, over time periods of the order of 1 s. The scattering and scintillation of emergent radio waves are ascribed to turbulent density irregularities transported by the ubiquitous solar wind streams. The spatial correlation length of density irregularities and the Fresnel radius of radio diffraction are two key parameters in determining the scintillation pattern. Such a scintillation pattern can be measured and correlated between multi-station radio telescopes on the Earth. Using the “phase-changing screen” scenario based on the Born approximation, the bulk-flow speed and turbulent spectrum of the solar wind streams can be extracted from the single-station power spectra fitting and the multi-station cross-correlation analysis. Moreover, a numerical computer-assisted tomography (CAT) model, iteratively fit to a large number of IPS measurements over one Carrington rotation, can be used to reconstruct the global velocity and density structures in the inner heliosphere for the purpose of space weather modelling and prediction. In this review, we interpret the underlying physics governing the IPS phenomenon caused by the solar wind turbulence, describe the power spectrum and cross correlation of IPS signals, highlight the space weather application of IPS-CAT models, and emphasize the significant benefits from international cooperation within the Worldwide IPS Stations (WIPSS) network.

Constraint on the minimally extended varying speed of light using time dilations in Type Ia supernovae

ABSTRACT The Friedmann–Lemaître–Robertson–Walker model establishes the correlation between redshifts and distances. It has a metric expansion of space. As a result, the wavelength of photons propagating through the expanding space is stretched, creating the cosmological redshift, z. It also relates the frequency of light detected by a local observer to that emitted from a distant source. In standard cosmology (i.e. a constant speed light model), this relation is given by a factor 1/(1 + z). However, this ratio is modified in the minimally extended varying speed of light model (meVSL, c = c0ab/4) as 1/(1 + z)1 − b/4. This time dilation effect is detected as the observed rate of the time variation in the intensity of emitted radiation. The spectra of Type Ia supernovae (SNe Ia) provide a reliable way to measure the apparent aging rate of distant objects. We use data on 13 high-redshift (0.28 ≤ z ≤ 0.62) SNe Ia to obtain b = 0.198 ± 0.415 at the 1-σ confidence interval. The current data is too sparse to give meaningful constrain on the meVSL and cannot distinguish the meVSL model from the standard model.

Deep Camera-Radar Fusion with an Attention Framework for Autonomous Vehicle Vision in Foggy Weather Conditions.

AVs are affected by reduced maneuverability and performance due to the degradation of sensor performances in fog. Such degradation can cause significant object detection errors in AVs' safety-critical conditions. For instance, YOLOv5 performs well under favorable weather but is affected by mis-detections and false positives due to atmospheric scattering caused by fog particles. The existing deep object detection techniques often exhibit a high degree of accuracy. Their drawback is being sluggish in object detection in fog. Object detection methods with a fast detection speed have been obtained using deep learning at the expense of accuracy. The problem of the lack of balance between detection speed and accuracy in fog persists. This paper presents an improved YOLOv5-based multi-sensor fusion network that combines radar object detection with a camera image bounding box. We transformed radar detection by mapping the radar detections into a two-dimensional image coordinate and projected the resultant radar image onto the camera image. Using the attention mechanism, we emphasized and improved the important feature representation used for object detection while reducing high-level feature information loss. We trained and tested our multi-sensor fusion network on clear and multi-fog weather datasets obtained from the CARLA simulator. Our results show that the proposed method significantly enhances the detection of small and distant objects. Our small CR-YOLOnet model best strikes a balance between accuracy and speed, with an accuracy of 0.849 at 69 fps.

Smart System for Visually Impaired People

Abstract: The main objective of the Smart System is to enable effortless and more unhindered movement for visually impaired people. People who are blind have a full life of responsibilities. However, being blind makes it difficult for them to carry out their duties. Many blind people move around and carry out their tasks using a conventional stick. Traditional sticks, however, do not detect impediments, making them useless for those who are blind. The blind individual is unaware of the types of obstructions or items in front of them. The blind person is unaware of both the object's size and the distance between him or her and it. Being blind makes it challenging to move about. They will be able to recognise anything to help persons with vision impairment by making many of their daily routines easy, pleasant, and organised. (A barrier for those who are blind). It is designed to make navigation easier for persons who are blind or visually impaired. People who are blind or have low eyesight can use it to comfortably and easily navigate and complete their everyday duties. a cutting-edge smartphone application that makes it easier for those with vision impairment to move around. The software approach suggested in this paper makes it easier and more pleasant for people with vision impairment to navigate their surroundings. The suggested solution employs a camera device— which may be a phone—and an application to assist blind and visually impaired persons in recognising things in their environment, such as TVs, tables, cars, and people this may help them avoid these things. The system will also determine the object's distance (measured in metres) and positioning inside the video feed that was collected (left, right, or centred). The device will therefore alert the user via sound from the smartphone.

Interactions between rodent visual and spatial systems during navigation.

Many behaviours that are critical for animals to survive and thrive rely on spatial navigation. Spatial navigation, in turn, relies on internal representations about one's spatial location, one's orientation or heading direction and the distance to objects in the environment. Although the importance of vision in guiding such internal representations has long been recognized, emerging evidence suggests that spatial signals can also modulate neural responses in the central visual pathway. Here, we review the bidirectional influences between visual and navigational signals in the rodent brain. Specifically, we discuss reciprocal interactions between vision and the internal representations of spatial position, explore the effects of vision on representations of an animal's heading direction and vice versa, and examine how the visual and navigational systems work together to assess the relative distances of objects and other features. Throughout, we consider how technological advances and novel ethological paradigms that probe rodent visuo-spatial behaviours allow us to advance our understanding of how brain areas of the central visual pathway and the spatial systems interact and enable complex behaviours.

Diversified and Realistic 3D Augmentation via Iterative Construction, Random Placement, and HPR Occlusion

In autonomous driving, data augmentation is commonly used for improving 3D object detection. The most basic methods include insertion of copied objects and rotation and scaling of the entire training frame. Numerous variants have been developed as well. The existing methods, however, are considerably limited when compared to the variety of the real world possibilities. In this work, we develop a diversified and realistic augmentation method that can flexibly construct a whole-body object, freely locate and rotate the object, and apply self-occlusion and external-occlusion accordingly. To improve the diversity of the whole-body object construction, we develop an iterative method that stochastically combines multiple objects observed from the real world into a single object. Unlike the existing augmentation methods, the constructed objects can be randomly located and rotated in the training frame because proper occlusions can be reflected to the whole-body objects in the final step. Finally, proper self-occlusion at each local object level and external-occlusion at the global frame level are applied using the Hidden Point Removal (HPR) algorithm that is computationally efficient. HPR is also used for adaptively controlling the point density of each object according to the object's distance from the LiDAR. Experiment results show that the proposed DR.CPO algorithm is data-efficient and model-agnostic without incurring any computational overhead. Also, DR.CPO can improve mAP performance by 2.08% when compared to the best 3D detection result known for KITTI dataset.

Catadioptric sensor concept with interlaced beam paths for imaging and pinpoint spectroscopy.

This paper presents the concept, optical design, and implementation of a catadioptric sensor for simultaneous imaging of a scene and pinpoint spectroscopy of a selected position, with object distances ranging from tens of centimeters to infinity and from narrow to wide adjustable viewing angles. The use of reflective imaging elements allows the implementation of folded and interlaced beam paths for spectroscopy and image acquisition, which enables a compact setup with a footprint of approximately 90m m×80m m. Although the wavelength range addressed extends far beyond the visible spectrum and reaches into the near infrared (∼400n m to 1000 nm), only three spherical surfaces are needed to project the intermediate image onto the image detector. The anamorphic imaging introduced by the folded beam path with different magnification factors in the horizontal and vertical directions as well as distortion can be compensated by software-based image processing. The area of the scene to be spectrally analyzed is imaged onto the input of an integrated miniature spectrometer. The imaging properties and spectroscopic characteristics are demonstrated in scenarios close to potential applications such as product sorting and fruit quality control.

3D Point Cloud Object Detection Algorithm Based on Temporal Information Fusion and Uncertainty Estimation

In autonomous driving, LiDAR (light detection and ranging) data are acquired over time. Most existing 3D object detection algorithms propose the object bounding box by processing each frame of data independently, which ignores the temporal sequence information. However, the temporal sequence information is usually helpful to detect the object with missing shape information due to long distance or occlusion. To address this problem, we propose a temporal sequence information fusion 3D point cloud object detection algorithm based on the Ada-GRU (adaptive gated recurrent unit). In this method, the feature of each frame for the LiDAR point cloud is extracted through the backbone network and is fed to the Ada-GRU together with the hidden features of the previous frames. Compared to the traditional GRU, the Ada-GRU can adjust the gating mechanism adaptively during the training process by introducing the adaptive activation function. The Ada-GRU outputs the temporal sequence fusion features to predict the 3D object in the current frame and transmits the hidden features of the current frame to the next frame. At the same time, the label uncertainty of the distant and occluded objects affects the training effect of the model. For this problem, this paper proposes a probability distribution model of 3D bounding box coordinates based on the Gaussian distribution function and designs the corresponding bounding box loss function to enable the model to learn and estimate the uncertainty of the positioning of the bounding box coordinates, so as to remove the bounding box with large positioning uncertainty in the post-processing stage to reduce the false positive rate. Finally, the experiments show that the methods proposed in this paper improve the accuracy of the object detection without significantly increasing the complexity of the algorithm.

A dynamical survey of the trans-Neptunian region − II. On the nature of chaotic diffusion

ABSTRACT On long enough time-scales, chaotic diffusion has the potential to significantly alter the appearance of a dynamical system. The Solar system is no exception: diffusive processes take part in the transportation of small bodies and provide dynamical pathways even for the distant trans-Neptunian objects to reach the inner Solar system. In this letter, we carry out a thorough investigation of the nature of chaotic diffusion. We analyse the temporal evolution of the mean squared displacement of 10 000 ensembles of test particles and quantify in each case the diffusion exponent (enabling the classification between normal, sub-, and superdiffusion), the generalized diffusion coefficient, and a characteristic diffusion time-scale, too. This latter quantity is compared with an entropy-based time-scale, and the two approaches are studied in light of direct computations as well. Our results are given in the context of two-dimensional maps, thereby facilitating the understanding of the relationship between the typical phase space structures and the properties of chaotic diffusion.