基于动态自适应空洞填补策略的快速消隐算法

给出了一个新的基于动态支次屏幕空洞填补策略的快速消隐算法,算法首先对场景进行均匀剖分,记录位于每个景物节点中的面片,并初始化屏幕空洞,在绘制时,从视点出发,通过视域四棱锥快速查询得到可能可见景物节点,进而根据空洞大小及其深度值确定面片数目的阈值,动态自适应地得到裁剪面,然后用硬件Ｚ－ｂｕｆｆｅｒ的方法进行绘制,并在屏幕四叉树缓冲器中检测出层次控制,插入到空洞列表中,不断得复上述过程,直到远裁剪面到     

数据驱动的层次场景序列识别模型研究（英文）

Scene classification is a complicated task, because it includes much content and it is difficult to capture its distribution.A novel hierarchical serial scene classification framework is presented in this paper. At first, we use hierarchical feature to present both the global scene and local patches containing specific objects. Hierarchy is presented by space pyramid match, and our own codebook is built by two different types of words. Secondly, we train the visual words by generative and discriminative methods respectively based on space pyramid match, which could obtain the local patch labels efficiently. Then, we use a neural network to simulate the human decision process, which leads to the final scene category from local labels. Experiments show that the hierarchical serial scene image representation and classification model obtains superior results with respect to accuracy.     

数据驱动的层次场景序列识别模型研究

针对层次场景图像序列,本文提出了一种数据驱动的基于快速序列视觉表述任务（rapid serial visual presentation task,RSVP）的场景识别模型. 首先基于金字塔模型提取三层尺度图像块,然后构建包括全局和局部特征的词汇字典,接着分别利用生成模型和判决模型训练视觉词汇,最后通过神经网络从图像块标记中获得场景类别. 实验表明算法能够获得更为精确的分类结果.     

Reprint of: Multi-scale 2D tracking of articulated objects using hierarchical spring systems

This paper presents a flexible framework to build a target-specific, part-based representation for arbitrary articulated or rigid objects. The aim is to successfully track the target object in 2D, through multiple scales and occlusions. This is realized by employing a hierarchical, iterative optimization process on the proposed representation of structure and appearance. Therefore, each rigid part of an object is described by a hierarchical spring system represented by an attributed graph pyramid. Hierarchical spring systems encode the spatial relationships of the features (attributes of the graph pyramid) describing the parts and enforce them by spring-like behavior during tracking. Articulation points connecting the parts of the object allow to transfer position information from reliable to ambiguous parts. Tracking is done in an iterative process by combining the hypotheses of simple trackers with the hypotheses extracted from the hierarchical spring systems.     

Multi-scale 2D tracking of articulated objects using hierarchical spring systems

This paper presents a flexible framework to build a target-specific, part-based representation for arbitrary articulated or rigid objects. The aim is to successfully track the target object in 2D, through multiple scales and occlusions. This is realized by employing a hierarchical, iterative optimization process on the proposed representation of structure and appearance. Therefore, each rigid part of an object is described by a hierarchical spring system represented by an attributed graph pyramid. Hierarchical spring systems encode the spatial relationships of the features (attributes of the graph pyramid) describing the parts and enforce them by spring-like behavior during tracking. Articulation points connecting the parts of the object allow to transfer position information from reliable to ambiguous parts. Tracking is done in an iterative process by combining the hypotheses of simple trackers with the hypotheses extracted from the hierarchical spring systems.     

Unsupervised segmentation of unknown objects in complex environments

This paper presents a novel object segmentation approach for highly complex indoor scenes. Our approach starts with a novel algorithm which partitions the scene into distinct regions whose boundaries accurately conform to the physical object boundaries in the scene. Next, we propose a novel perceptual grouping algorithm based on local cues (e.g., 3D proximity, co-planarity, and shape convexity) to merge these regions into object hypotheses. Our extensive experimental evaluations demonstrate that our object segmentation results are superior compared to the state-of-the-art methods.     

Generating compact representations of static scenes by means of 3D object hierarchies

This paper presents a new heuristic algorithm for computing a compact hierarchical representation of the objects contained in a 3D static scene. The algorithm first builds a fully-connected adjacency graph that keeps the costs of grouping the different pairs of objects of the scene. Afterward, the graph’s minimum spanning tree is computed and its edges sorted in ascending order according to their cost. Next, from that sorted list, a cost-based clustering technique is applied, thus generating new objects at a higher level in the hierarchy. A new object can be defined after merging two or more objects according to their corresponding linking costs. The algorithm starts over by generating a new adjacency graph from those new objects, along with the objects that could not be merged before. The iterative process is applied until an adjacency graph with a single object is obtained. The latter is the root of the hierarchical representation. Balance and coherence of the hierarchy, in which spatially close objects are also structurally close, is achieved by defining an appropriate cost function. The proposed technique is evaluated upon several 3D scenes and compared to a previous technique. In addition, the benefits of the proposed technique with respect to techniques based on octrees and kd-trees are analyzed in terms of a practical application.     

基于OpenGL的三维建筑设计组件的设计与实现

本文提出了一种面向对象的支持三维图形可重用的组件层次设计方法，分析了组件的性能、设计方法和图元算法，实现了基于OpenGL的支持三维虚拟场景、建模和运动仿真的组件设计，描述了实体的运动层次链接关系和数据结构，并实现了虚拟环境的建筑物建模和运动仿真。     

数据中心三维可视化场景编辑器的设计

针对当前数据中心的三维可视化场景重复开发造成复用性较差的问题,提出了数据中心三维可视化场景编辑器.借助三维引擎技术,以仿真、立体、互动实时的方式为管理者提供一个完整的、可视化、网络化的虚拟环境管理设计平台.可以高效灵活的创建数据中心3D场景,用于场景建模和数据中心的辅助设计.可视化编辑器基于Unity3D引擎和Web技术进行搭建,提供直观的浏览器操作界面和环境实时监控系统,解决了三维场景远程实时查看数据中心监控等问题.用户可以借此快速搭建三维可视化场景,减少重复开发.在提供其他3D模型基础上,此编辑器也能够广泛用于其他非数据中心可视化场景的搭建和编辑.     

基于深度学习的视觉目标检测技术综述

视觉目标检测旨在定位和识别图像中存在的物体,属于计算机视觉领域的经典任务之一,也是许多计算机视觉任务的前提与基础,在自动驾驶、视频监控等领域具有重要的应用价值,受到研究人员的广泛关注。随着深度学习技术的飞速发展,目标检测取得了巨大的进展。首先,本文总结了深度目标检测在训练和测试过程中的基本流程。训练阶段包括数据预处理、检测网络、标签分配与损失函数计算等过程,测试阶段使用经过训练的检测器生成检测结果并对检测结果进行后处理。然后,回顾基于单目相机的视觉目标检测方法,主要包括基于锚点框的方法、无锚点框的方法和端到端预测的方法等。同时,总结了目标检测中一些常见的子模块设计方法。在基于单目相机的视觉目标检测方法之后,介绍了基于双目相机的视觉目标检测方法。在此基础上,分别对比了单目目标检测和双目目标检测的国内外研究进展情况,并展望了视觉目标检测技术发展趋势。通过总结和分析,希望能够为相关研究人员进行视觉目标检测相关研究提供参考。     

Volume graphics

Volume graphics, which employs a volume buffer of voxels for 3D scene representation, is discussed. Volume graphics offers advantages over surface graphics: it is viewpoint independent, insensitive to scene and object complexity, and suitable for the representation of sampled and simulated data sets. Moreover, geometric objects can be mixed with these data sets. Volume graphics supports the visualization of internal structures and lends itself to the realization of block operations, constructive solid geometry modeling, irregular voxel sizes, and hierarchical representation. The problems associated with the volume buffer representation (such as discreteness, memory size, processing time, and loss of geometric representation) are discussed     

Texture segmentation using hierarchical wavelet decomposition

This paper presents a texture segmentation algorithm based on a hierarchical wavelet decomposition. Using Daubechies four-tap filter, an original image is decomposed into three detail images and one approximate image. The decomposition can be recursively applied to the approximate image to generate a lower resolution of the pyramid. The segmentation starts at the lowest resolution using the K-means clustering scheme and textural features obtained from various sub-bands. The result of segmentation is propagated through the pyramid to a higher resolution with continuously improving the segmentation. The lower resolution levels help to build the contour of the segmented texture, while higher levels refine the process, and correct possible errors.     

真实场景中基于体表示的目标外形和纹理获取

传统的基于图像的三维重建方法中,图像间的相关特征匹配是影响重建模型质量和精度的主要因素之一。提出一种基于体表示的真实目标的重建方法,回避了二维图像间的特征匹配问题,简化了建模的复杂度。该方法首先提取目标物的轮廓信息;其次单向单层遍历场景空间中目标物的最小三维包围盒,利用目标物固有的颜色信息不变性判断体元反向投影的一致性,从而获取目标的三维信息;最后利用获取的三维信息绘制得到真实目标的逼真模型。实验结果表明该方法建模精度较高,真实感强。     

基于光照模型和视觉特性的半色调彩色图像的实时仿真

利用人类视觉系统的生理特性,提出了一种基于光照模型的半色调模式的真实感彩色图像的实时仿真方法,该方法合三维目标的成像过程,将场景中视觉2°视锥小区域的平均灰度信息转换为明暗象素点阵模式,从而实时地生成半色调模式的实感彩色图像。在微机上进行了编程设计和实验,实验结果表明,本文提出的方法不但可产生三维视觉效果舒适的真实感图像处理速度极快,图像数据量也大大降低,这为场景图像的实时仿真、输出和图像传输等提供先进的实用的数字技术。     

Automatic Lighting Design using a Perceptual Quality Metric

Lighting has a crucial impact on the appearance of 3D objects and on the ability of an image to communicate information about a 3D scene to a human observer. This paper presents a new automatic lighting design approach for comprehensible rendering of 3D objects. Given a geometric model of a 3D object or scene, the material properties of the surfaces in the model, and the desired viewing parameters, our approach automatically determines the values of various lighting parameters by optimizing a perception-based image quality objective function. This objective function is designed to quantify the extent to which an image of a 3D scene succeeds in communicating scene information, such as the 3D shapes of the objects, fine geometric details, and the spatial relationships between the objects.
Our results demonstrate that the proposed approach is an effective lighting design tool, suitable for users without expertise or knowledge in visual perception or in lighting design.     

3DGIS中空间数据可视化的研究与应用

空间数据可视化是当前3DGIS领域的研究热点之一。提出了一种面向对象的空间数据可视化模型，基于金字塔模型来组织和调度DEM（数字高程模型）、DOM（数字正射影像）等栅格数据，并引入矢量数据参数化3D建模思想，实现了矢量地物数据的三维建模与可视化。在此基础上，借助虚拟现实技术，基于OpenGL实现了一个3DGIS原型系统，具备空间数据的真实感可视化表达、3D场景实时漫游、交互查询等功能。最后给出了基于该原型系统为军事与民用领域开发的应用实例。