Efficient single-pixel imaging encrypted transmission based on 3D Arnold transformation

Single-pixel imaging(SPI)can transform 2D or 3D image data into 1D light signals,which offers promising prospects for image compression and transmission.However,during data communication these light signals in public channels will easily draw the attention of eavesdroppers.Here,we introduce an efficient encryption method for SPI data transmission that uses the 3D Arnold transformation to directly disrupt 1D single-pixel light signals and utilizes the elliptic curve encryption algorithm for key transmission.This encryption scheme immediately employs Hadamard patterns to illuminate the scene and then utilizes the 3D Arnold transformation to permutate the 1D light signal of single-pixel detection.Then the transformation parameters serve as the secret key,while the security of key exchange is guaranteed by an elliptic curve-based key exchange mechanism.Compared with existing encryption schemes,both computer simulations and optical experiments have been conducted to demonstrate that the proposed technique not only enhances the security of encryption but also eliminates the need for complicated pattern scrambling rules.Additionally,this approach solves the problem of secure key transmission,thus ensuring the security of information and the quality of the decrypted images.

Overview of 3D Human Pose Estimation

3D human pose estimation is a major focus area in the field of computer vision,which plays an important role in practical applications.This article summarizes the framework and research progress related to the estimation of monocular RGB images and videos.An overall perspective ofmethods integrated with deep learning is introduced.Novel image-based and video-based inputs are proposed as the analysis framework.From this viewpoint,common problems are discussed.The diversity of human postures usually leads to problems such as occlusion and ambiguity,and the lack of training datasets often results in poor generalization ability of the model.Regression methods are crucial for solving such problems.Considering image-based input,the multi-view method is commonly used to solve occlusion problems.Here,the multi-view method is analyzed comprehensively.By referring to video-based input,the human prior knowledge of restricted motion is used to predict human postures.In addition,structural constraints are widely used as prior knowledge.Furthermore,weakly supervised learningmethods are studied and discussed for these two types of inputs to improve the model generalization ability.The problem of insufficient training datasets must also be considered,especially because 3D datasets are usually biased and limited.Finally,emerging and popular datasets and evaluation indicators are discussed.The characteristics of the datasets and the relationships of the indicators are explained and highlighted.Thus,this article can be useful and instructive for researchers who are lacking in experience and find this field confusing.In addition,by providing an overview of 3D human pose estimation,this article sorts and refines recent studies on 3D human pose estimation.It describes kernel problems and common useful methods,and discusses the scope for further research.

3D Model Construction and Ecological Environment Investigation on a Regional Scale Using UAV Remote Sensing

The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture,spatial res-olution,and multiple parameter categories,which is challenging to achieve using satellite remote sensing.Considering the convenient,facilitative,and flexible characteristics of UAV(unmanned air vehicle)remote sensing tech-nology,this study selects a campus as a typical research area and uses the Pegasus D2000 equipped with a D-MSPC2000 multi-spectral camera and a CAM3000 aerial camera to acquire oblique images and multi-spectral data.Using professional software,including Context Capture,ENVI,and ArcGIS,a 3D(three-dimensional)campus model,a digital orthophoto map,and multi-spectral remote sensing map drawing are realized,and the geometric accuracy of typical feature selection is evaluated.Based on a quantitative remote sensing model,the campus ecological environment assessment is performed from the perspectives of vegetation and water body.The results presented in this study could be of great significance to the scientific management and sustainable development of regional natural resources.

PCA-based 3D Shape Reconstruction of Human Foot Using Multiple Viewpoint Cameras

This paper describes a multiple camera-based method to reconstruct the 3D shape of a human foot. From a foot database, an initial 3D model of the foot represented by a cloud of points is built. The shape parameters, which can characterize more than 92% of a foot, are defined by using the principal component analysis method. Then, using ＂active shape models＂, the initial 3D model is adapted to the real foot captured in multiple images by applying some constraints （edge points＇ distance and color variance）. We insist here on the experiment part where we demonstrate the efficiency of the proposed method on a plastic foot model, and also on real human feet with various shapes. We propose and compare different ways of texturing the foot which is needed for reconstruction. We present an experiment performed on the plastic foot model and on human feet and propose two different ways to improve the final 3D shapers accuracy according to the previous experiments＇ results. The first improvement proposed is the densification of the cloud of points used to represent the initial model and the foot database. The second improvement concerns the projected patterns used to texture the foot. We conclude by showing the obtained results for a human foot with the average computed shape error being only 1.06 mm.

Survey of 3D modeling using depth cameras

Three-dimensional(3D)modeling is an important topic in computer graphics and computer vision.In recent years,the introduction of consumer-grade depth cameras has resulted in profound advances in 3D modeling.Starting with the basic data structure,this survey reviews the latest developments of 3D modeling based on depth cameras,including research works on camera tracking,3D object and scene reconstruction,and high-quality texture reconstruction.We also discuss the future work and possible solutions for 3D modeling based on the depth camera.

Camera Calibration for 3D Color Scanning System Using Virtual 3D Model

Instead of traditionally using a 3D physical model with many control points on it, a calibration plate with printed chess grid and movable along its normal direction is implemented to provide large area 3D control points with variable Z values. Experiments show that the approach presented is effective for reconstructing 3D color objects in computer vision system.

Accurate 3D geometry measurement for non-cooperative spacecraft with an unfocused light-field camera

This work explores an alternative 3D geometry measurement method for non-cooperative spacecraft guiding navigation and proximity operations.From one snapshot of an unfocused light-field camera, the 3D point cloud of a non-cooperative spacecraft can be calculated from sub-aperture images with the epipolar plane image(EPI) based light-field rendering algorithm.A Chang'e-3 model(7.2 cm×5.6 cm×7.0 cm) is tested to validate the proposed technique.Three measurement distances(1.0 m, 1.2 m, 1.5 m) are considered to simulate different approaching stages.Measuring errors are quantified by comparing the light-field camera data with a high precision commercial laser scanner.The mean error distance for the three cases are 0.837 mm, 0.743 mm, and 0.973 mm respectively, indicating that the method can well reconstruct 3D geometry of a non-cooperative spacecraft with a densely distributed 3D point cloud and is thus promising in space-related missions.

三维模型与视频素材的完美结合——AE插件Element 3D与Track camera技术的实际应用

相较于传统的AE针对3D动画合成中出现的各种繁琐的操作,如摄像机同步、光影匹配等等,Element 3D都可以让特效师直接在AE里完成,而不需要考虑摄像机和光影迁移等诸多问题。配合AE内置的Tracker camera功能,更是可以完成各类复杂的三维后期合成特效,大大降低了以往摄像机反求搭建三维场景的难度和渲染负担。

虚拟3D技术中摄像机云台姿态高精度定位测试方法研究

本文着力于摄像机云台高精度定位测试方法研究,使其在虚拟3D图像合成过程中,可通过控制摄像机云台动作完成虚拟3D图像合成.本系统在摄像机云台上加持多路传感器,感受摄像机云台姿态变化;通过以高速控制芯片为核心的主控箱模块进行传感器数据采集与数据处理;解析同步信号并同步向3D合成工作站发送云台姿态信息,最终完成3D图像合成.经过实验,系统可以高速、准确地采集到多路高精度传感器数据并同步发送至3D合成工作站,且具有良好的稳定性,能够满足摄影所需的长期开机的工作要求.

3-D计算机视觉系统的高精度摄象机定标算法—DLTEAⅡ

本文在分析计算机视觉系统中摄象机几何模型的基础上,修正了光学镜头畸变模型使之与数字成象系统相配合,提出了一个非常适合于3—D计算机视觉系统的通用高精度摄象机定标方法:增强型直接线性变换—误差拟合算法(DLTEAⅡ).实验表明,使用普通CCD摄象机的立体视觉系统经DLTEAⅡ定标后,在300mm×200mm视场和0.8m～0.9m深度范围内其三维定位的绝对精度分别为dx<0.03mm,dy<0.04mm和dz<0.09mm,相对精度为视场大小和深度的1/10000.本文所提出的定标方法在三维计算机视觉、智能机器人、工业自动化生产、近景摄影测量和军事等领域有着广泛的应用前景.

Real-Time Characterization of Crystal Shape and Size Distribution Based on Moving Window and 3D Imaging in a Stirred Tank

Crystal shape distribution, i.e. the multidimensional size distribution of crystals, is of great importance to their down-stream processing such as in filtration as well as to the end-use properties including the dissolution rate and bioavailability for crystalline pharmaceuticals. Engineering crystal shape and shape distribution requires knowledge about the growth behavior of different crystal facets under varied operational conditions e.g. supersaturations. Measurement of the facet growth rates and growth kinetics of static crystals in a crystallizer without stirring has been reported previously. Here attention is given to study on real-time characterization of the 3D facet growth behavior of crystals in a stirred tank where crystals are constantly moving and rotating. The measurement technique is stereo imaging and the crystal shape reconstruction is based on a stereo imaging camera model. By reference to a case study on potash alum crystallization, it is demonstrated that the crystal size and shape distributions (CSSD) of moving and rotating potash alum crystals in the solution can be reconstructed. The moving window approach was used to correlate 3D face growth kinetics with supersaturation (in the range 0.04 - 0.12) given by an ATR FTIR probe. It revealed that {100} is the fastest growing face, leading to a rapid reduction of its area, while the {111} face has the slowest growth rate, reflected in its area continuously getting larger.

Survey on depth and RGB image-based 3D hand shape and pose estimation

The field of vision-based human hand three-dimensional(3D)shape and pose estimation has attracted significant attention recently owing to its key role in various applications,such as natural human computer interactions.With the availability of large-scale annotated hand datasets and the rapid developments of deep neural networks(DNNs),numerous DNN-based data-driven methods have been proposed for accurate and rapid hand shape and pose estimation.Nonetheless,the existence of complicated hand articulation,depth and scale ambiguities,occlusions,and finger similarity remain challenging.In this study,we present a comprehensive survey of state-of-the-art 3D hand shape and pose estimation approaches using RGB-D cameras.Related RGB-D cameras,hand datasets,and a performance analysis are also discussed to provide a holistic view of recent achievements.We also discuss the research potential of this rapidly growing field.

A Skeletal Camera Network for Close-range Images with a Data Driven Approach in Analyzing Stereo Configuration

Structure-from-Motion(SfM)techniques have been widely used for 3D geometry reconstruction from multi-view images.Nevertheless,the efficiency and quality of the reconstructed geometry depends on multiple factors,i.e.,the base-height ratio,intersection angle,overlap,and ground control points,etc.,which are rarely quantified in real-world applications.To answer this question,in this paper,we take a data-driven approach by analyzing hundreds of terrestrial stereo image configurations through a typical SfM algorithm.Two main meta-parameters with respect to base-height ratio and intersection angle are analyzed.Following the results,we propose a Skeletal Camera Network(SCN)and embed it into the SfM to lead to a novel SfM scheme called SCN-SfM,which limits tie-point matching to the remaining connected image pairs in SCN.The proposed method was applied in three terrestrial datasets.Experimental results have demonstrated the effectiveness of the proposed SCN-SfM to achieve 3D geometry with higher accuracy and fast time efficiency compared to the typical SfM method,whereas the completeness of the geometry is comparable.

不同光照条件下CCD相机时间噪声和空间噪声的研究

在用CCD相机进行目标探测时,多数情况下目标的背景具有一定的照度,这个照度会对探测结果产生影响。为了了解背景对探测结果的影响,通过建立CCD相机三维噪声模型及其测试系统,在不同光照条件下对CCD相机的时间噪声和空间噪声进行了测量与分析。给出了测试系统的结构框图和部分测试结果,得到了对CCD输出质量产生主要影响的噪声以及时间噪声和空间噪声随光照度变化的规律。测试结果表明:随着CCD相机光敏面光照度的提高,空间噪声和时间噪声均升高,符合CCD相机的实际性能。

不同光照条件下数字CCD相机响应不均匀性研究

从理论上分析了数字CCD相机光电响应不均匀性的原因,通过建立数字CCD相机响应不均匀性测试系统和三维模型,推导出了数字CCD相机响应不均匀性的计算公式,对数字CCD相机的响应不均匀性进行测量与分析,给出了测试系统的结构框图和部分测试结果.

双CCD系统在三维面形测量中的应用

讨论了用于直升机着陆激光雷达地形测量系统的双目立体视觉方法,并利用双CCD系统实现了对激光器照射到固定目标表面上任意单点的三维空间坐标测量。首先应用最小二乘法对既定标定点三维空间坐标的测量进行了分析,提出了标定点列的优化原则;然后分析了正交约束条件对测距误差的影响,并建立了双CCD激光测距实验系统。理论分析和实验结果表明,选择经分布优化的标定点列和采用正交约束条件可以使目标点的各向测距误差在总体上得到优化,从而使得双CCD系统在近距测量中有较高的测量精度,适合于三维面形的测量。

一种简便的单目CCD摄像机标定方法

对数学形态学中腐蚀和膨胀原理进行研究,提出针对常用的对称十字二维平面标定板图像的特征点提取算法。结合改进的Tasi两步法,选取经典的带一阶径向畸变的小孔摄像机模型,对MV-1300UC数字CCD摄像机进行标定。实验结果表明,该方法能够达到较高标定精度,平均标定误差为0.025 3 mm,且计算效率高,易于实现。

Robot trajectory planning for autonomous 3D reconstruction of cockpit in aircraft final assembly testing

The trend towards automation and intelligence in aircraft final assembly testing has led to a new demand for autonomous perception of unknown cockpit operation scenes in robotic collaborative airborne system testing.To address this demand,a robotic automated 3D reconstruction cell which enables to autonomously plan the robot end-camera’s trajectory is developed for image acquisition and 3D modeling of the cockpit operation scene.A continuous viewpoint path planning algorithm is proposed that incorporates both 3D reconstruction quality and robot path quality into optimization process.Smoothness metrics for viewpoint position paths and orientation paths are introduced together for the first time in 3D reconstruction.To ensure safe and effective movement,two spatial constraints,Domain of View Admissible Position(DVAP)and Domain of View Admissible Orientation(DVAO),are implemented to account for robot reachability and collision avoidance.By using diffeomorphism mapping,the orientation path is transformed into 3D,consistent with the position path.Both orientation and position paths can be optimized in a unified framework to maximize the gain of reconstruction quality and path smoothness within DVAP and DVAO.The reconstruction cell is capable of automatic data acquisition and fine scene modeling,using the generated robot C-space trajectory.Simulation and physical scene experiments have confirmed the effectiveness of the proposed method to achieve highprecision 3D reconstruction while optimizing robot motion quality.

不同光照条件下数字CCD相机响应不均匀性研究

数字CCD相机光电输入输出响应不均匀特性是其用于光束远近场能量分布测量的重要参数,因此研究数字CCD相机的响应不均匀性,是保障激光参数测量系统测量精度的关键技术环节。从理论上分析了数字CCD相机光电响应不均匀性的原因,通过建立数字CCD相机响应不均匀性测试系统和三维模型,推导出了数字CCD相机相应不均匀性的计算公式,对数字CCD相机的响应不均匀性进行测量与分析,给出了测试系统的结构框图和部分测试结果。

Rapid Texture Mapping from Image Sequences for Building Geometry Model

An effective approach, mapping the texture for building model based on the digital photogrammetric theory, is proposed. The easily-acquired image sequences from digital video camera on helicopter are used as texture resource, and the correspondence between the space edge in building geometry model and its line feature in image sequences is determined semi-automatically. The experimental results in production of three-dimensional data for car navigation show us an attractive future both in efficiency and effect.