Principles Of Vision Research Articles

A defense method based on attention mechanism against traffic sign adversarial samples

A traditional neural network cannot realize the invariance of image rotation and distortion well, so an attacker can fool the neural network by adding tiny disturbances to an image. If traffic signs are attacked, automatic driving will probably be misguided, leading to disastrous consequences. Inspired by the principle of human vision, this paper proposes a defense method based on an attentional mechanism for traffic sign adversarial samples. In this method, the affine coordinate parameters of the target objects in the images are extracted by a CNN, and then the target objects are redrawn by the coordinate mapping model. In this process, the key areas in the image are extracted by the attention mechanism, and the pixels are filtered by interpolation. Our model simulates the daily behavior of human beings, making it more intelligent in the defense against the adversarial samples. Experiments show that our method has a strong defense ability for traffic sign adversarial samples generated by various attack methods. Compared with other defense methods, our method is more universal and has a strong defense ability against a variety of attacks. Moreover, our model is portable and can be easily implanted into neural networks in the form of defense plug-ins.

VIA “Chervona Ruta” in the context of variety- ensemble performance of Ukraine

The aim of the article is to clarify the artistic role of the ensemble “Chervona Ruta” in the context of Ukrainian musical culture. The relevance of the study lies in the development of principles of a new vision, trends in the development of the ensemble “Chervona Ruta” in the context of Ukrainian pop and ensemble performance and its role in the development of musical culture of Ukraine. The methodology of this study is the application of comparative-historical method, which allows us to trace the historical context of the ensemble and the context of the development of pop and ensemble art of Ukraine. The chronological method allows to determine the stages of formation and development of the team on the example of the analysis of concert and performance activities of the ensemble. Vocal and pop performance on the examplebof the ensemble “Chervona Ruta” appears as a dynamic cultural and artistic phenomenon. The song repertoire of the ensemble appears as a translator of the identity of Ukrainian culture, which is confirmed by the presence of folk intonations and the involvement of appropriatebinstruments. The study of the processes of formation and development of ensembles allows us to identify the traditions of Ukrainian pop music, which is a prerequisite for the formation and development of musical art in Ukraine. Despite the existing achievements in the study of ensemble performance, the issues of the influence of ensemble work on Ukrainian artistic music culture remain insufficiently studied, which highlights the need for a comprehensive analysis of the specifics of pop vocal and ensemble performance, especially the band “Chervona Ruta” as a creative phenomenon of pop ensemble. The creative path of the ensemble “Chervona Ruta” began a new stage in the formation of pop song repertoire, which differs from the previous significant changes in genre richness, functional features and new means of performance. The popularization of Ukrainian pop song contributed to the development of television, the improvement of sound recording and reproducing equipment, the emergence of electromusical instruments. All this contributed to the emergence of numerous amateur vocal and instrumental ensembles – a hallmark of a new era in the development of popular music. The advent of VIA brought new ways of artistic expression to the stage – new timbre paints, the use of electromusical instruments with their specifics, the use of various electronic systems, the strange sound of voices in extreme tension. Conclusions. Ensemble art in various genre and stylistic forms has always played a significant role in social life and has enjoyed the widest popularity among composers, performers and listeners in all historical epochs and in general remains popular today. The rise and prosperity of VIA coincided with a period of intensive scientific and technical discoveries – radio engineering, electronics, sound recording. Participants of vocal-instrumental ensembles can be called musicians-performers of a new type, they are at the same time singers, musicians, actors and authors. The new domestic VIA combined the features of big beat and enriched them with national elements, in their programs there is a tendency to synthesize with theater, choreography. A new youth spectator stood out from the former regular audience of the stage, the regulatory functions of the mass media increased.

Layout Design of Medical Terminal Interface Combining User-Oriented andGenetic Algorithm

<p indent="0mm">In order to achieve the optimal interface design of the public terminal while improving user experience, this paper proposes an interface layout method that combines user orientation and a genetic algorithm. According to this method, the subjective cognition of users and their objective vision principle are integrated before conversion into a layout index. With the index of the interface layout scheme taken as the independent variable and the user experience value as the dependent variable, the cognitive relationship between the interface layout index and subjective user experience was modeled as a computable function. The expansion solution space was searched after the interface layout features were encoded using the slicing tree method. The specific steps include generating tree structure, determining the cutting method to obtain the best section tree, and adjusting the element nodes to identify the most satisfactory layout. With the registration interface and payment interface of the medical public terminal as an example, this method was applied to optimize its layout and then verified through a usability test. According to the experimental results, the usability indicators of the optimized interface layout was improved more significantly compared with the initial interface, suggesting the effectiveness of this method in the application of medical terminal interface design scenarios. Moreover, the generative auxiliary design of this kind is conducive to reducing the workload placed on designers and to enhancing efficiency.

High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

Application of integrated binocular stereo vision measurement and wireless sensor system in athlete displacement test

Based on binocular stereo vision measurement and wireless sensing theory, this paper studies the measurement and analysis methods of athletes' movement displacement parameters. The main purpose is to explore the relationship between sports biomechanical parameters. The analysis reveals the laws of athletes 'movements, and provides theoretical guidance on athletes' attitude recognition and physical training. Based on the principle of binocular stereo vision, a non-contact displacement measurement system was developed. The displacement measurement system uses template matching to extract the image coordinates of the measurement points and restore the spatial coordinates of the measurement points through European 3D reconstruction, which improves the practicality of the measurement system. In the cantilever beam vibration test, the traditional displacement sensor and binocular image displacement measurement system are used to simultaneously measure the cantilever beam displacement. The experimental results show that the integrated displacement measurement system in this paper has higher accuracy and better stability.

Method of using non-specific target to complete structured light plane calibration

The accuracy of the line structured light measurement system is determined by the calibration results of the structured light plane Existing structured light calibration methods usually need to fabricate a specific target with high manufacturing precision to complete the calibration. In the real environment, how to calibrate the line structured light plain without a specific target becomes a key issue. In this paper, a stereo vision calibration (SVC) method is proposed and used to complete the structured light calibration with non-specific targets. It adopts the principle of stereo vision to calculate all point clouds projected on the target by structured light, and then the parameters of the structured light plane are optimized based on the probability distribution during point clouds processing. Taking 304 steel plate, aluminum round can, and book as non-specific targets, the accuracy of the plane calibrated by SVC method is measured. The minimum average measurement error is about 0.068 mm by comparing the nominal values with the measurement values of the checkerboard and different workpieces. It indicates that the SVC method can acquire the high-precision calibration with non-specific targets.

Panoramic Stereo Imaging of a Bionic Compound-Eye Based on Binocular Vision.

With the rapid development of the virtual reality industry, one of the bottlenecks is the scarcity of video resources. How to capture high-definition panoramic video with depth information and real-time stereo display has become a key technical problem to be solved. In this paper, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed. Combined with the real-time processing algorithm of multi detector mosaic panoramic stereo imaging image, a panoramic stereo real-time imaging system is developed. Firstly, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed, and the space coordinate calibration platform of ultra-high precision panoramic camera based on theodolite angle compensation function is constructed. The projection matrix of adjacent cameras is obtained by solving the imaging principle of binocular stereo vision. Then, a real-time registration algorithm of multi-detector mosaic image and Lucas-Kanade optical flow method based on image segmentation are proposed to realize stereo matching and depth information estimation of panoramic imaging, and the estimation results are analyzed effectively. Experimental results show that the stereo matching time of panoramic imaging is 30 ms, the registration accuracy is 0.1 pixel, the edge information of depth map is clearer, and it can meet the imaging requirements of different lighting conditions.

A 3D Machine Vision-Enabled Intelligent Robot Architecture

In this paper, the principle of camera imaging is studied, and the transformation model of camera calibration is analyzed. Based on Zhang Zhengyou’s camera calibration method, an automatic calibration method for monocular and binocular cameras is developed on a multichannel vision platform. The automatic calibration of camera parameters using human-machine interface of the host computer is realized. Based on the principle of binocular vision, a feasible three-dimensional positioning method for binocular target points is proposed and evaluated to provide binocular three-dimensional positioning of target in simple environment. Based on the designed multichannel vision platform, image acquisition, preprocessing, image display, monocular and binocular automatic calibration, and binocular three-dimensional positioning experiments are conducted. Moreover, the positioning error is analyzed, and the effectiveness of the binocular vision module is verified to justify the robustness of our approach.

Использование технологии сверточных нейронных сетей в сегментации объектов изображения

The classification and description of the tasks solved using computer vision technologies are given. The use of neural networks to create systems for selecting objects in an image stream is considered in more detail. It also explains what is meant by training a neural network and discusses in detail the main stages of machine learning. The features of the application of convolutional neural networks for the segmentation of image objects, i.e., the selection of objects in the image, are indicated. The choice of the neural network architecture has been made, which has the property of extracting basic information from the image. The characteristics of the segmentation problem and the basic principles of computer vision are given. Conclusions are given on the possible application of the developed neural network model for solving various applied problems.

Analysis and Optimization of Computer Trajectory Based on Compound Eye Vision System

With the rapid development of science and technology, people have higher and higher requirements for target detection technology, which requires us to solve the disadvantages of traditional cameras, such as the difficulty of panoramic photography and continuous tracking motion. However, compound eye insects have a visual system composed of fewer neurons, which can achieve rapid detection and capture of objects of interest. Therefore, based on the principle of compound eye vision, a bionic compound eye panoramic detection system is designed in this paper, which can realize panoramic real-time detection through multiple sub eye cameras. Through the compound eye vision system, we can accurately locate the pan tilt controller, which can provide a comprehensive panoramic motion image. Through the principle of automatic windowing, we can acquire the image of moving area by multi-layer window. Then, through the relevant image processing methods, such as binarization, median filtering, spatial filtering, moving object detection, edge detection and other methods, we can get a relatively clear moving object contour and trajectory analysis, which can achieve full field of view, high sensitivity detection and tracking.

Perceptions of provincial and district level managers\u2019 on the policy implementation of school oral health in South Africa

BackgroundAlthough school oral health programmes have been ongoing for years, there is little evidence to show how their policy elements are governed or translated into tangible implementation activities and population outcomes at the district level. The need for such a study is heightened by the persistent burden of oral health conditions and unmet oral treatment needs of South Africa’s children. This study therefore sought to describe provincial and district level managers’ perceptions of school oral health policy, and to identify gaps and conditions needed for successful policy implementation.MethodsThis was an exploratory qualitative study where eight oral health managers from the Gauteng provincial and district offices were purposively sampled. Data were collected using interviews and a policy review rubric. The 10 Siddiqi governance principles framework was used to guide the data analysis.ResultsThe managers’ perceptions and the policy document review indicated that national policy covered the principles of strategic vision, responsiveness to health needs, equity and inclusivity with clarity; however these principles were not translated consistently by the managers at a local level. Policy gaps were identified in the areas of stakeholder involvement, accountability, reliable information systems and ethical guidelines. Much of the gaps in policy translation were attributed to inadequate human resources and poor communication processes by the national leadership to support district level implementation.ConclusionsThere were inconsistencies in policy awareness and translation in the districts and hence an in-depth review of the policy translation gaps is paramount to its efficient resolution in the context of resource and capacity limitations. Furthermore, optimizing multi-sectoral participation and identifying shared, novel and practical solutions to policy translation impediments is necessary.

Fuzzy model based on local injection of MTX combined with traditional Chinese medicine guided by ultrasound intervention to treat CSP

In view of pregnancy at the uterine scar after cesarean section, there is an urgent need to find a conservative treatment mode with drugs that can improve the success rate of treatment, shorten the conservative treatment time, and cause little harm to the body. This research combines ultrasound intervention technology to construct a fuzzy model to comprehensively evaluate the clinical effects of traditional Chinese medicine combined with western medicine in the treatment of CSP. Moreover, this research combines the current application algorithms of machine vision to explain the relevant principles of ultrasound interventional vision. In addition, this research uses the background subtraction method to extract the target, and uses the machine vision algorithm to extract the ultrasonic detection target object. Finally, this research adjusts the control parameters according to the fuzzy control, and outputs the optimal control plan with BP network training. The results of this study show that the combination of Chinese and Western medicines in the treatment of uterine scars after cesarean section has the advantages of small gestational sacs, short pregnancy, and low blood β-HCG, and it has the advantages of less pain, economy, fewer side effects, and successfully preserves the uterus. Therefore, it is worthy of clinical application.

FP-Nets for Blind Image Quality Assessment

Feature-Product networks (FP-nets) are a novel deep-network architecture inspired by principles of biological vision. These networks contain the so-called FP-blocks that learn two different filters for each input feature map, the outputs of which are then multiplied. Such an architecture is inspired by models of end-stopped neurons, which are common in cortical areas V1 and especially in V2. The authors here use FP-nets on three image quality assessment (IQA) benchmarks for blind IQA. They show that by using FP-nets, they can obtain networks that deliver state-of-the-art performance while being significantly more compact than competing models. A further improvement that they obtain is due to a simple attention mechanism. The good results that they report may be related to the fact that they employ bio-inspired design principles.

Research on target feature extraction and location positioning with machine learning algorithm

Abstract The accurate positioning of target is an important link in robot technology. Based on machine learning algorithm, this study firstly analyzed the location positioning principle of binocular vision of robot, then extracted features of the target using speeded-up robust features (SURF) method, positioned the location using Back Propagation Neural Networks (BPNN) method, and tested the method through experiments. The experimental results showed that the feature extraction of SURF method was fast, about 0.2 s, and was less affected by noise. It was found from the positioning results that the output position of the BPNN method was basically consistent with the actual position, and errors in X, Y and Z directions were very small, which could meet the positioning needs of the robot. The experimental results verify the effectiveness of machine learning method and provide some theoretical support for its further promotion and application in practice.

The technology of 3D curved glass hot-pressing film of new bionic nanomaterial

In order to solve the problems of uneven thickness, poor hardness and wear resistance of traditional curved glass coating technology, a new three-dimensional (3D) curved glass hot-pressing technology of bionic nanomaterials was studied. According to the principle of machine vision, whether the curved glass to be coated meets the requirements of hot-pressing was checked. In addition, a biomimetic nanomaterial film was prepared through the mixed-solvent method. According to the characteristics of 3D curved glass at different temperatures, the parameters of the hot-press film machine were set, and the hot-press film machine was used to complete the research on the 3D curved glass hot-press film technology. Compared with the traditional curved glass film technology, the experimental results show that the new bionic nanomaterial 3D curved glass hot-pressing film technology can achieve uniform coating on the glass surface, and the hardness and wear resistance of the film are better than those of films produced by the traditional coating technology, showing that the new technology has great practical application value.

Computer Vision in the Operating Room: Opportunities and Caveats.

Effectiveness of computer vision techniques has been demonstrated through a number of applications, both within and outside healthcare. The operating room environment specifically is a setting with rich data sources compatible with computational approaches and high potential for direct patient benefit. The aim of this review is to summarize major topics in computer vision for surgical domains. The major capabilities of computer vision are described as an aid to surgical teams to improve performance and contribute to enhanced patient safety. Literature was identified through leading experts in the fields of surgery, computational analysis and modeling in medicine, and computer vision in healthcare. The literature supports the application of computer vision principles to surgery. Potential applications within surgery include operating room vigilance, endoscopic vigilance, and individual and team-wide behavioral analysis. To advance the field, we recommend collecting and publishing carefully annotated datasets. Doing so will enable the surgery community to collectively define well-specified common objectives for automated systems, spur academic research, mobilize industry, and provide benchmarks with which we can track progress. Leveraging computer vision approaches through interdisciplinary collaboration and advanced approaches to data acquisition, modeling, interpretation, and integration promises a powerful impact on patient safety, public health, and financial costs.

Algorithm for epipolar geometry and correcting monocular stereo vision based on a plane mirror

Based on the epipolar geometry of binocular stereo vision, the epipolar geometry of monocular stereo vision with a plane mirror is studied. This paper analyses the imaging principle of monocular stereo vision with a plane mirror, the epipolar constraint equation for monocular stereo vision is deduced, and the constraint relationship between two image points of an object in an image is discussed. We also discuss the epipolar correction of monocular stereo vision and the results of both simulated and real experiments. The experiment shows that the epipolar correction of monocular stereo vision proposed in this paper is completely correct and feasible, which provides the basis for the follow-up study of monocular stereo vision with a plane mirror.

Polarimetric dynamic vision sensor p(DVS) principles

This contribution relates to the activities of the TC-19 on “Imaging Signals and Systems.” In a rapidly changing global economy, experiencing an unparalleled integration of science and technology, the development of efficient imaging systems is of extreme significance. The scope of TC-19 is to exchange and disseminate knowledge as well as bridge multidisciplinary areas leading to the creation of new knowledge and establish global collaborative multidisciplinary opportunities by tightening collaborations among government, industry, academia, and healthcare industry. The Committee explores a variety of computer vision and visualization systems spanning from medical imaging to defense, industry, and consumer electronics. These imaging systems use statistical or sophisticated artificial algorithms and require the integration of several technological and computational disciplines, such as detector physics and phenomenology, calibration, metrology, data acquisition, data analysis, image processing, feature extraction, and classification. Often, coexisting competing design requirements and trade-off introduce significant challenges to the design of imaging technologies. For instance, Autonomous Vehicles (AV)s, Unmanned Aerial Vehicles (UAV)s, Unmanned Underwater Vehicle (UUV)s, microsatellites, nanosatellites, and picosatellites for defense and civilian applications are characteristic examples with trade-off between design requirements for high performance imaging and maintaining low-power consumption, high-data transmission, low storage and memory, and reduced payload. To address these competing design challenges, TC-19 introduced the polarimetric neuromorphic vision principles which blend bioinspired principles such as human cognition with the vision of certain arthropods, and aquatic biological species.

Three-dimensional spine morphology measuring technology for daily surface monitoring

In order to conduct surface monitoring of the three-dimensional spine morphology of the human body in daily life, a spine morphology measuring method using "single camera, multi-view" to construct stereo vision is proposed. The images of the back of the human body with landmarks of spinous process are captured from multiple angles by moving a single camera, and based on the "Zhang Zhengyou calibration method" and the triangulation principle of binocular stereo vision, the spatial conversion matrices corresponding to each other between all images and the 3D coordinates of the landmarks are calculated. Then the spine evaluation angle used to evaluate the spine morphology is further calculated. The tests' results showed that the spine evaluation angle error of this method is within ±3°, and the correlation between the results and the X-ray film Cobb angles is 0.871. The visual detection algorithm used in this paper is non-radioactive, and because only one camera is used in the measurement process and there is no need to pre-set the camera's shooting pose, the operation is simple. The research results of this article can be used in a mobile phone-based intelligent detection system, which will be suitable for the group survey of scoliosis in communities, schools, families and other occasions, as well as for the long-term follow-up of confirmed patients. This will provide a reference for doctors to diagnose the condition, predict the development trend of the condition, and formulate treatment plans.

Monocular image depth prediction without depth sensors: An unsupervised learning method

Monocular image depth prediction is an interesting challenge in three-dimensional (3D) perception, the purpose of which is to obtain the geometric features of 3D scenes from two-dimensional (2D) images. At present, the deep learning method for monocular depth prediction has yielded good results, but this approach treats it as a supervised deep regression problem. A significant weakness of current methods is the need to collect reams of depth measurement data in actual scenarios for training. In this paper, we design a novel convolutional neural network (CNN) with an encoding and decoding structure to estimate the depth map from monocular RGB images based on basic principles of binocular stereo vision, and use rectified stereo pairs to train our network from scratch in an unsupervised learning method without any depth data. We also explore a new upsampling strategy to improve the output resolution, and introduce a new dynamic optimization strategy to enhance the training speed and prediction accuracy. Extensive experiments on the publicly available KITTI and Cityscapes datasets demonstrate that our approach is more accurate than competing methods. The findings of the proposed methodology illustrate that our CNN model can be utilized as depth completion from LIDAR images.