Editing Soft Shadows in a Digital Photograph

In this article, we develop tools for shadow modification in images where a shadowed region is characterized by soft boundaries with varying sharpness along the shadow edges. Modeling shadow edges presents an interesting challenge because they can vary from infinitely sharp edges for shadows produced by a point light source to extremely soft edges for shadows produced by large area light sources. We propose an entirely image-based shadow editing tool for a single-input image. This technique for modeling, editing, and rendering shadow edges in a photograph or a synthetic image lets users separate the shadow from the rest of the image and make arbitrary adjustments to its position, sharpness, and intensity. These machine-adjustable photographs can offer interactivity that might improve images' expressiveness and help us investigate the influence of boundary sharpness on the perception of object-to-object contact, as well as understand how humans assess shadows to estimate object height above a ground plane     

Camera calibration and geo-location estimation from two shadow trajectories

The position of a world point’s solar shadow depends on its geographical location, the geometrical relationship between the orientation of the sunshine and the ground plane where the shadow casts. This paper investigates the property of solar shadow trajectories on a planar surface and shows that camera parameters, latitude, longitude and shadow casting objects’ relative height ratios can be estimated from two observed shadow trajectories. One contribution is to recover the horizon line and metric rectification matrix from four observations of two shadow tips. The other contribution is that we use the design of an analemmatic sundial to get the shadow conic and furthermore recover the camera’s geographical location. The proposed method does not require the shadow casting objects or a vertical object to be visible in the recovery of camera calibration. This approach is thoroughly validated on both synthetic and real data, and tested against various sources of errors including noise, number of observations, objects locations, and camera orientations. We also present applications to image-based metrology.     

Shadow Casting Out Of Plane (SCOOP) Candidates for Human and Vehicle Detection in Aerial Imagery

In this paper, we propose a method for detecting humans and vehicles in imagery taken from a UAV. This is a challenging problem due to a limited number of pixels on target, which makes it more difficult to distinguish objects from background clutter, and results in much larger search space. We propose a method for constraining the search based on a number of geometric constraints obtained from the metadata. Specifically, we obtain the orientation of ground plane normal, the orientation of shadows cast by out of plane objects in the scene, and the relationship between object heights and the size of their corresponding shadows. We use the aforementioned information in a geometry-based shadow, and ground-plane normal blob detector, which provides an initial estimation for locations of shadow casting out of plane (SCOOP) objects in the scene. These SCOOP candidate locations are then classified as either human or clutter using a combination of wavelet features and a Support Vector Machine. To detect vehicles, we similarly find potential vehicle candidates by combining SCOOP and inverted-SCOOP candidates and then classify them using wavelet features and SVM. Our method works on a single frame, and unlike motion detection based methods, it bypasses the entire pipeline of registration, motion detection, and tracking. This method allows for detection of stationary and slowly moving humans and vehicles while avoiding the search across the entire image, allowing accurate and fast localization. We show impressive results on sequences from VIVID and CLIF datasets and provide comparative analysis.     

基于ICA特征的运动阴影检测算法

为防止运动阴影在视频图像序列中被错误地检测为目标,必须提高阴影检测算法的准确性和普适性。为此,从独立分量分析(ICA)的原理及其特性出发,提出一种基于空间变换技术的运动阴影检测算法。该算法通过对视频序列建立高斯混合背景模型产生自适应背景,利用ICA技术对其进行空间变换提取特征,再通过背景与当前帧图像对应像素点在特征空间的位置特征来分类运动阴影与前景目标。实验结果表明该方法能够较好地抑制噪声,减少光照变化的影响,准确地检测出阴影。     

Tessellation‐Independent Smooth Shadow Boundaries

We propose an efficient and light‐weight solution for rendering smooth shadow boundaries that do not reveal the tessellation of the shadow‐casting geometry. Our algorithm reconstructs the smooth contours of the underlying mesh and then extrudes shadow volumes from the smooth silhouettes to render the shadows. For this purpose we propose an improved silhouette reconstruction using the vertex normals of the underlying smooth mesh. Then our method subdivides the silhouette loops until the contours are sufficiently smooth and project to smooth shadow boundaries. This approach decouples the shadow smoothness from the tessellation of the geometry and can be used to maintain equally high shadow quality for multiple LOD levels. It causes only a minimal change to the fill rate, which is the well‐known bottleneck of shadow volumes, and hence has only small overhead.     

基于光照无关图的阴影去除方法

为了在检测目标时排除阴影的干扰,首先论述了光照无关图的原理及其重要性质,然后在此基础上提出了一种基于光照无关图的阴影去除方法。该方法根据光学成像原理通过对图像进行变换来得到一幅与光照无关的灰度图,以达到去除阴影的目的。同时针对该方法需事先测定摄像机的光照无关角的不便之处,还提出了基于直方图统计的摄像机光照无关角判定法则。通过对大量不同场景下视频监控图像的实际测试结果表明,基于光照无关图的阴影去除方法以及基于直方图统计的光照无关角判定方法,可以有效去除目标阴影,并可准确分割目标。     

Lighting Simulation of Augmented Outdoor Scene Based on a Legacy Photograph

We propose a novel approach to simulate the illumination of augmented outdoor scene based on a legacy photograph. Unlike previous works which only take surface radiosity or lighting related prior information as the basis of illumination estimation, our method integrates both of these two items. By adopting spherical harmonics, we deduce a linear model with only six illumination parameters. The illumination of an outdoor scene is finally calculated by solving a linear least square problem with the color constraint of the sunlight and the skylight. A high quality environment map is then set up, leading to realistic rendering results. We also explore the problem of shadow casting between real and virtual objects without knowing the geometry of objects which cast shadows. An efficient method is proposed to project complex shadows (such as tree's shadows) on the ground of the real scene to the surface of the virtual object with texture mapping. Finally, we present an unified scheme for image composition of a real outdoor scene with virtual objects ensuring their illumination consistency and shadow consistency. Experiments demonstrate the effectiveness and flexibility of our method.     

平面阴影算法研究与实现

阴影对提升图形的真实感具有重要意义。探讨了平面阴影生成算法，针对平面阴影算法在实际应用中的缺点，利用OpenGL的模板缓冲技术实现阴影裁剪，利用基于截锥体的裁剪矩阵消除假影和反影现象，并利用OpenGL累积缓冲技术实现软阴影。较好解决了平面阴影算法的缺点，程序计算量小、效率高，图形的真实感和场景的可视化效果得以提升，达到良好的效果。     

GPS coordinates estimation and camera calibration from solar shadows

In this paper, we discuss the issue of camera parameter estimation (intrinsic and extrinsic parameters), along with estimation of the geo-location of the camera by using only the shadow trajectories. By observing stationary objects over a period of time, it is shown that only six points on the trajectories formed by tracking the shadows of the objects are sufficient to estimate the horizon line of the ground plane. This line is used along with the extracted vertical vanishing point to calibrate the stationary camera. The method requires as few as two shadow casting objects in the scene and a set of six or more points on the shadow trajectories of these objects. Once camera intrinsic parameters are recovered, we present a novel application where one can accurately determine the geo-location of the camera up to a longitude ambiguity using only three points from these shadow trajectories without using any GPS or other special instruments. We consider possible cases where this ambiguity can also be removed if additional information is available. Our method does not require any knowledge of the date or the time when the images are taken, and recovers the date of acquisition directly from the images. We demonstrate the accuracy of our technique for both steps of calibration and geo-temporal localization using synthetic and real data.     

结合多种特征的高分辨率遥感影像阴影检测

针对现有的阴影检测算法对较亮阴影和较暗地物中的阴影不能同时较好地检测等问题, 提出一种结合多种特征的高分辨率遥感影像阴影检测方法.该算法首先结合主成分分析、颜色特征和直方图的分割构建多种阈值检测条件, 然后综合多种特征来进行遥感影像阴影的初步检测, 最后通过分析RGB模型在阴影与非阴影地物上的差别, 利用颜色特性最终检测出阴影区域.实验结果表明, 本文算法能有效检测较亮阴影和较暗地物中的阴影.与现有方法相比, 较亮阴影的平均总错误率从水平集法的31.85%降至24.61%, 较暗地物中阴影的平均总错误率从自动检测法的37.75%降至23.30%.     

基于波谱角和掩膜的卫星影像阴影去除研究

详细分析了卫星影像的阴影来源,以遮挡物类型和传感器探测特点为依据对阴影进行了分类和研究。分析了波谱角法检测阴影的技术特点和操作方式,研究了掩膜技术提取阴影的方法,并提出采用分波段线性扩展和滤波的手段去除阴影。通过ETM数据的试验分析,验证了波谱角和掩膜技术可以在去除陆地卫星影像阴影中发挥重要作用。     

融合阴影图和深度划分阴影体的阴影渲染算法

阴影图算法可以简单、快速地渲染硬阴影,但该算法渲染的硬阴影会在边缘区域出现锯齿状走样。受此影响,基于阴影图算法渲染的柔和阴影,在小尺寸半影区域依然可能会出现锯齿状走样。因此,要渲染无走样的柔和阴影,需要精确计算阴影边缘区域的着色点对点光源的可见性。深度划分阴影体算法可以精确地计算着色点对点光源的可见性,但其不仅在效率上不及阴影图算法,还无法实现柔和阴影渲染。针对上述问题,提出一种融合阴影图和深度划分阴影体的阴影渲染算法,对处于阴影边缘区域的着色点,使用深度划分阴影体算法精确计算该着色点对点光源的可见性;对其他着色点,使用阴影图算法快速计算该着色点对点光源的可见性。最后,将着色点的可见性值存储在可见性图中并滤波即可实现无走样柔和阴影的渲染。     

双层SVM的阴影检测与基于窗口融合的阴影恢复

阴影的存在对于机器视觉的分析如区域的边缘提取,目标识别以及图像匹配等往往具有一定的干扰,而现如今提出的算法往往并不能很好地处理阴影区域的纹理和边缘。主要针对静态阴影图像提出了一种成对区域阴影检测和恢复的方法。阴影检测：通过提取阴影和非阴影区域之间边缘两侧颜色、纹理、方向和距离特征采用双层SVM训练器对阴影区域进行检测,不仅能检测出阴影区域,同时能够检测出与此阴影区域在同一表面的非阴影区域。阴影恢复：采用提出的自适应步长的窗口匹配方法获得阴影区域的采样窗口的最佳匹配窗口,采用窗口融合的方式初步恢复阴影区域,然后使用提出的迭代的方式对图像纹理进行增强,最后用快速修复方法（FMM）去除阴影与非阴影区域的微弱边缘。Opencv仿真证明,这样不仅可以提高阴影区域检测准确率,而且能够很好地保存纹理信息。     

Exponential Soft Shadow Mapping

In this paper we present an image‐based algorithm to render visually plausible anti‐aliased soft shadows in real time. Our technique employs a new shadow pre‐filtering method based on an extended exponential shadow mapping theory. The algorithm achieves faithful contact shadows by adopting an optimal approximation to exponential shadow reconstruction function. Benefiting from a novel overflow free summed area table tile grid data structure, numerical stability is guaranteed and error filtering response is avoided. By integrating an adaptive anisotropic filtering method, the proposed algorithm can produce high quality smooth shadows both in large penumbra areas and in high frequency sharp transitions, meanwhile guarantee cheap memory consumption and high performance.     

单幅图像下不同阴影强度的阴影去除

阴影是由于场景的照明不一致而出现在图像中的自然现象。当物体的透光度不同或由不同光源照射会在图像中产生不同强度的阴影。因此,对具有不同阴影强度的图像阴影去除进行了研究。通过用户交互得到阴影掩模,接下来检测具有围绕阴影边界的可变间隔和长度的样本强度分布,这避免了不均匀边界引起的伪影。然后结合超像素分割算法和FCM_S聚类算法对阴影部分进行区域合并,用于阴影和图像边界处尺度的估计。为了恢复阴影部分光照,采用图像修复算法传播阴影尺度场。最后,得到阴影去除后的图像,并进行色彩校正。为了证明该算法的优越性能,与其他算法进行定量比较,结果有所提升。     

Building‐based damage detection due to earthquake using the watershed segmentation of the post‐event aerial images

This paper presents an approach for detecting the damaged buildings due to earthquake using the watershed segmentation of the post‐event aerial images. The approach utilizes the relationship between the buildings and their cast shadows. It is based on an idea that if a building is damaged, it will not produce shadows. The cast shadows of the buildings are detected through an immersion‐based watershed segmentation. The boundaries of the buildings are available and stored in a GIS as vector polygons. The vector‐building boundaries are used to match the shadow casting edges of the buildings with their corresponding shadows and to perform assessments on a building‐specific manner. For each building, a final decision on the damage condition is taken, based on the assessments carried out for that building only. The approach was implemented in Golcuk, one of the urban areas most strongly hit by the 1999 Izmit, Turkey earthquake. To implement the approach, a system called the Building‐Based Earthquake Damage Assessment System was developed in MATLAB. Of the 284 buildings processed and analysed, 229 were correctly labelled as damaged and undamaged, providing an overall accuracy of 80.63%.     

基于移动区域的快速车辆检测

提出一种快速的移动车辆目标识别新方法。该方法由移动区域检测、阴影检测和边缘检测三部分组成。首先,采用自适应背景更新的方法在图像中快速检测出移动区域;然后,以此为基础建立阴影的粗模型,阴影检测时只对该区域内的图像采用基于HSV颜色空间的方法进行分析处理;最后,对移动区域和阴影区域进行边缘检测,从移动区域中去除阴影区域,从而准确区分真实车辆和阴影。实验表明,该方法有效地提高了车辆检测效率,能满足实时性要求。     

一种入侵容忍的密钥分发方案

提出了一种入侵容忍的密钥分发方案。在该方案中，密钥的生成由若干服务器通过秘密共享机制协作完成，每个服务器并不知道所生成的密钥，只持有其秘密份额。密钥分发的过程同样基于秘密共享实现，由用户获取各服务器所持有的秘密份额进行恢复从而获取密钥。分析表明，该方案中不存在唯一失效点，即使一定数量的服务器被攻击者控制后，系统仍然可以完成密钥分发。     

Essential secret image sharing scheme with the same size of shadows

Secret image sharing is a method to decompose a secret image into shadow images (shadows) so that only qualified subset of shadows can be used to reconstruct the secret image. Usually all shadows have the same importance. Recently, an essential SIS (ESIS) scheme with different importance of shadows was proposed. All shadows are divided into two group: essential shadows and non-essential shadows. In reconstruction, the involved shadows should contain at least a required number of shadows, including at least a required number of essential shadows. However, there are two problems in previous ESIS scheme: unequal size of shadows and concatenation of sub-shadow images. These two problems may lead to security vulnerability and complicate the reconstruction. In this paper, we propose a novel ESIS scheme based on derivative polynomial and Birkhoff interpolation. A single shadow with the same-size is generated for each essential and non-essential participant. The experimental results demonstrate that our scheme can avoid above two problems effectively.