动态变形表面的四维测量

提出一种在双目视觉中利用随机三角形纹理进行动态变形表面四维测量的方法。生成随机的三角形纹理,将纹理转印到纸、布等需要进行测量的对象表面上;用标定的两个同步相机拍摄表面的动态变形过程,获得两个同步的图像序列。使用提出的方法,检测每个图像上的三角形;使用提出的三角形描述符和三角形极线约束方法,匹配第一帧图像上的三角形,并根据匹配的结果,测量物体表面在第一帧中的三维信息;根据所测的信息生成每个三角形的局部三维拓扑结构;在两个同步的图像序列中追踪三角形,得到四维测量的结果,并且利用局部拓扑结构检测并修复出现的错误。模拟实验、实际数据实验,验证了该方法的有效性和可行性。     

Bidirectional reflectance of a rough anisotropic surface

The goal of our work was to demonstrate that the usual assumptions of isotropy and symmetry of the bidirectional reflectance factor (BRF) are not valid for a specific anisotropic ground surface. Two methods illustrating this point are presented. The first method is based on goniometer measurements, and the second method uses a Monte Carlo algorithm. The results of both methods were analysed at different wavelengths and angular configurations. For the surface studied here, they showed that the BRF was significantly asymmetric with respect to the principal plane. In the extreme case, the difference between the two sides of the principal plane reached almost 30% of the mean reflectance value.     

Evaluation of apparent surface reflectance estimation methodologies

The estimation of apparent surface reflectance values from imaging spectroscopy data requires a correction for the efTects of the intervening atmosphere. Four methods of estimating apparent surface reflectance have been evaluated, the empirical line method and three methods of radiative transfer modelling. To compare the results of these correction methodologies two high albedo targets, of identified composition, were selected. The empirical line method was found to be sensitive to errors in locating and spectral variations within the ground survey targets and also target height differences. The radiative transfer modelling techniques gave relatively similar results, reasonably close to the library spectra. This study indicates that radiative transfer modelling using only atmospheric information derived from the imaging spectroscopy data, while still not as sensitive as correction methods using additional ground and atmospheric information, can satisfactorily correct the atmospheric elfects involved in estimating apparent surface reflectance, allowing the identification of the major diagnostic absorption features.     

A deformable surface model for real-time water drop animation

A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.     

A fast approach to deformable surface 3D tracking

Deformable surface 3D tracking is a severely under-constrained problem and great efforts have been made to solve it. A recent state-of-the-art approach solves this problem by formulating it as a second order cone programming (SOCP) problem. However, one drawback of this approach is that it is time-consuming. In this paper, we propose an effective method for 3D deformable surface tracking. First, we formulate the deformable surface tracking problem as a linear programming (LP) problem. Then, we solve the LP problem with an algorithm which converges superlinearly rather than bisection algorithm whose convergence speed is linear. Our experimental studies on synthetic and real data have demonstrated the proposed method can not only reliably recover 3D structures of surfaces but also run faster than the state-of-the-art method.     

基于GPU的非牛顿流体自由表面绘制方法

提出一种基于GPU的非牛顿流体自由表面绘制方法。首先,分析了非牛顿流体的物理模型,将流体的运动规律用合理的数学表达式进行描述;其次,针对非牛顿流体的特点设计了合理的可视模型,提出了流体运动及自由表面的绘制方法,并且设计了相应的GPU实现算法;最后的实验证明了算法在合理的时间内能完全逼真的对非牛顿流体的自由表面进行真实的再现。算法充分吸收了以往方法的优点,采用了合理的数学模型,并利用GPU的运算特性实现了非牛顿流体自由表面的绘制,在绘制效果和效率上较以往算法都有较大改进。     

Comparative analysis of urban reflectance and surface temperature

Urban environmental conditions are strongly dependent on the biophysical properties and radiant thermal field of the land cover elements in the urban mosaic. Observations of urban reflectance and surface temperature provide valuable constraints on the physical properties that are determinants of mass and energy fluxes in the urban environment. Consistencies in the covariation of surface temperature with reflectance properties can be parameterized to represent characteristics of the surface energy flux associated with different land covers and physical conditions. Linear mixture models can accurately represent Landsat ETM+ reflectances as fractions of generic spectral endmembers that correspond to land surface materials with distinct physical properties. Modeling heterogeneous land cover as mixtures of rock and/or soil Substrate, Vegetation and non-reflective Dark surface (SVD) generic endmembers makes it possible to quantify the dependence of aggregate surface temperature on the relative abundance of each physical component of the land cover, thereby distinguishing the effects of vegetation abundance, soil exposure, albedo and shadowing. Comparing these covariations in a wide variety of urban settings and physical environments provides a more robust indication of the global variability in these parameter spaces than could be inferred from a single study area. A comparative analysis of 24 urban areas and their non-urban peripheries illustrates the variability in the urban thermal fields and its dependence on biophysical land surface components. Contrary to expectation, moderate resolution intra-urban variations in surface temperature are generally as large as regional surface heat island signatures in these urban areas. Many of the non-temperate urban areas did not have surface heat island signatures at all. However, the multivariate distributions of surface temperature and generic endmember fractions reveal consistent patterns of thermal fraction covariation resulting from land cover characteristics. The Thermal-Vegetation (TV) fraction space illustrates the considerable variability in the well-known inverse correlation between surface temperature and vegetation fraction at moderate (< 100 m) spatial resolutions. The Thermal-Substrate (TS) fraction space reveals energetic thresholds where competing effects of albedo, illumination and soil moisture determine the covariation of maximum and minimum temperature with illuminated substrate fraction. The dark surface endmember fraction represents a fundamental ambiguity in the radiance signal because it can correspond to either absorptive (e.g. low albedo asphalt), transmissive (e.g. deep clear water) or shadowed (e.g. tree canopy shadow) surfaces. However, in areas where dark surface composition can be inferred from spatial context, the different responses of these surfaces may still allow them to be distinguished in the thermal fraction space.     

Using surface variability characteristics for segmentation of deformable 3D objects with application to piecewise statistical deformable model

To cope with the small sample size problem in the construction of Statistical Deformable Models (SDM), this paper proposes two novel measures that quantify the similarity of the variability characteristics among deforming 3D meshes. These measures are used as the basis of our proposed technique for partitioning a 3D mesh for the construction of piecewise SDM in a divide-and-conquer strategy. Specifically, the surface variability information is extracted by performing a global principal component analysis on the set of sample meshes. An iterative face clustering algorithm is developed for segmenting a mesh that favors grouping triangular faces having similar variability characteristics into a same mesh component. We apply the proposed mesh segmentation algorithm to the construction of piecewise SDM and evaluate the representational ability of the resulting piecewise SDM through the reconstruction of unseen meshes. Experimental results show that our approach outperforms several state-of-the-art methods in terms of the representational ability of the resulting piecewise SDM as evaluated by the reconstruction accuracy.     

Influence of soil surface roughness on soil bidirectional reflectance

The non-Lambertian behaviour of soil surfaces depends on its roughness at micro-scale and larger scales, as well as on the incident angle of the direct solar beam on the surface. A geometrical model, taking into account the diffuse as well as the specular component of energy leaving soil surfaces in the visible and near-infrared, is used in the paper to describe the influence of soil surface roughness, caused by soil aggregates or soil clods, on the soil bidirectional reflectance distribution. A rough soil surface in the model is simulated by equalsized opaque spheroids lying on a horizontal surface. The model was tested in outdoor conditions on artificially formed soil surfaces made of two spectrally different soil materials: a mineral loam, and a loam with high organic matter content. The spectral data were measured by a field radiometer in the three SPOT (HRV) bands. The model predicts that at specific illumination conditions, soils surfaces with the highest roughness, expressed by the minimum distances between soil aggregates, can show lower variation of reflectance in the view zenith angle function than soil surfaces of a lower roughness.     

Dynamic harmonic fields for surface processing

Harmonic fields have been shown to provide effective guidance for a number of geometry processing problems. In this paper, we propose a method for fast updating of harmonic fields defined on polygonal meshes, enabling real-time insertion and deletion of constraints. Our approach utilizes the penalty method to enforce constraints in harmonic field computation. It maintains the symmetry of the Laplacian system and takes advantage of fast multi-rank updating and downdating of Cholesky factorization, achieving both speed and numerical stability. We demonstrate how the interactivity induced by fast harmonic field update can be utilized in several applications, including harmonic-guided quadrilateral remeshing, vector field design, interactive geometric detail modeling, and handle-driven shape editing and animation transfer with a dynamic handle set.     

Spectral shape-based temporal compositing algorithms for MODIS surface reflectance data

Spectral similarity metrics have previously been used to select representative spectra from a class for use in spectral mixture modeling. Since the tasks of spectral selection for spectral mixture modeling and spectral selection for temporal compositing are similar, these metrics may have utility for temporal compositing. This paper explores the use of two spectral similarity metrics, endmember average root mean square error (EAR) and minimum average spectral angle (MASA), for constructing temporal composites. EAR and MASA compositing algorithms were compared against four previously used algorithms, including maximum NDVI, minimum view zenith angle, minimum blue, and median red. A total of 10 different algorithms were used to create 16-day composites of Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data over a 6-year period. Algorithm performance was assessed based on short-term temporal variability in spectral reflectance and in a selection of indices, both within a southwestern California study area and within five land-cover class subsets. EAR compositing produced the lowest variability for 4 out of 7 MODIS bands, as measured by the root mean square of time series residuals. MASA or EAR compositing produced the lowest root mean square residual values for all of the tested indices. To assess how compositing algorithms might affect remote sensing correlations with biophysical variables, correlations between indices calculated from different composites and live fuel moisture were compared. Correlations between indices and live fuel moisture were higher for shape-based composites compared with the standard composites.     

Quality assessment of Landsat surface reflectance products using MODIS data

Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat images for the 2000 epoch. As surface reflectance likely will be a standard product for future Landsat missions, the approach developed in this study can be adapted as an operational quality assessment system for those missions.     

动态变形表面三维重建方法研究与实现*

提出一种对可变性物体表面的动态变形过程进行三维重建的方法.将图像序列第一帧中物体表面划分成多个图像块,利用优化函数寻找每个图像块在所有帧中的对应关系,最终实现物体运动过程的三维重建;完成每一帧的三维重建后,根据图像关联度和局部拓扑结构对结果进行错误检测,并对出错块进行重新优化.模拟实验、实际数据实验以及与同类算法的比较,验证了该方法的有效性和可行性.     

A simulation of bidirectional reflectance distributions for various surface microstructures

Abstract

A simple model was developed to allow the determination of the bidirectional reflectance distribution function along the Sun's azimuthai plane for surfaces with roughness described by a repetition or microstructures. A modular surface unit is utilized representing a wide range of microstructures. The simulation is based on equations accounting for the shadowing and obstruction geometries which determine the reflectance properties of the surface. This Letter presents some of the equations developed and typical directional reflectance curves produced by the simulation.     

Correction of hyperspectral reflectance measurements for surface objects and direct sun reflection on surface waters

Satellite, airborne, or platform-based remote sensing reflectance measurements of aquatic targets are frequently compromised by water-surface effects such as specular sun reflection (glint) or transient objects like buoys or boats. For temporal or spatial data series where sub-surface reflectance is of interest, the elimination of affected data may require time-consuming manual selection of spectra and substantial data loss. Here, we present a method for the automated elimination of data points containing surface objects or strong sun reflection, which is based on the spectral slope in the ultra-violet to blue (350 nm to 450 nm). To minimize data loss, an automated sun glint correction combining two previously published methods is also presented. The method operates by subtracting a glint spectrum by means of a regression curve characterized from low to medium glint data points and is further automated by selecting these low glint data on the basis of the oxygen absorption depth in the near infrared (NIR). The elimination and correction algorithms facilitate rapid automated processing of large bio-optical data sets for both spatial and temporally resolved remote-sensing reflectance data sets. Here we demonstrate their efficacy on a three-month data set of hourly light field measurements from a fixed platform in the northwest Mediterranean.     

Visualizing multiple fields on the same surface

A long-standing problem in the field of visualization is the ability to display many overlaid data sets. Researchers have developed successful techniques that show multiple 3D fields by layering sparse similar glyphs. My colleagues and I at the University of North Carolina have investigated this problem for a number of years. Our driving application has been the display of data sets from scanned-probe and scanned-electron microscopes, which led us to concentrate on the display of multiple scalar fields. Although several of our first approaches were initially successful, they failed to scale to more than three or four data sets. So that others will not be tempted to follow the same course, I begin by presenting the argument for, preliminary successes with, and reasons for the eventual downfall of our initial approach. I then describe the key concept that enables successful techniques.     

Evaluation of measurement errors in ground surface reflectance for satellite calibration

Abstract

One of the more efficient methods used for in-flight calibration of Earth resource satellites is based on measurements performed at ground level on a test site. An experimental study has been conducted in La Crau Sèche (south east France), where a calibration site for SPOT satellites is intended. The accuracy of the calibration depends, critically, on the accuracy of ground bidirectional reflectance factor (BDRF) measurements.

All of the different sources of error are analysed. These are due to two series of factors depending on the characteristics of the radiometer (electronic charac teristics, absolute calibration, angular setting of the radiometer) and of the ground surface (the spectral, spatial, angular and temporal variability of the BDRF). The relative weight of these different causes of error is determined from experimental data. This analysis shows that, besides the well-known disturbing factors such as the calibration of the radiometer and the spatial variability of the BDRF, two other factors can introduce large measurement errors: the spectral and angular variability of reflectance of the site.

This detailed analysis of the different causes of error is not only valid for the calibration of a satellite, but it can also be used to draw up guidelines for performing accurate BDRF measurements in natural conditions for any application.     

Tool condition monitoring using reflectance of chip surface and neural network

A wide variety of tool condition monitoring techniques has been introduced in recent years. Among them, tool force monitoring, tool vibration monitoring and tool acoustics emission monitoring are the three most common indirect tool condition monitoring techniques. Using multiple intelligent sensors, these techniques are able to monitor tool condition with varying degrees of success. This paper presents a novel approach for the estimation of tool wear using the reflectance of cutting chip surface and a back propagation neural network. It postulates that the condition of a tool can be determined using the surface finish and color of a cutting chip. A series of experiments has been carried out. The experimental data obtained was used to train the back propagation neural network. Subsequently, the trained neural network was used to perform tool wear prediction. Results show that the prediction is in good agreement with the flank wear measured experimentally.     

Retrieval of surface directional reflectance properties using ground level multiangle measurements

Knowledge of the directional reflectance properties of natural surfaces such as soils and vegetation canopies is essential for classification studies and canopy model inversion. Atmospheric correction schemes, using various levels of approximation, are described to retrieve surface bidirectional reflectance factors (BRFs) and directionalhemispherical reflectances (albedos) from multiangle radiance measurements taken at ground level. The retrieval schemes are tested on simulated data incorporating realistic surface BRFs and atmospheric models containing aerosols. Sensitivity of the atmospherically corrected BRFs and associated directional-hemispherical reflectances to various aerosol properties and the sun-view geometry is illustrated. A measurement strategy for obtaining highly accurate surface reflectance properties also is examined in the context of instrument radiometric calibration, knowledge of the atmospheric properties, and sun-view angular coverage.