Comparison of Camera Motion Estimation Methods for 3D Reconstruction of Infrastructure

Camera motion estimation is one of the most significant steps for structure-from-motion (SFM) with a monocular camera. The normalized 8-point, the 7-point, and the 5-point algorithms are normally adopted to perform the estimation, each of which has distinct performance characteristics. Given unique needs and challenges associated to civil infrastructure SFM scenarios, selection of the proper algorithm directly impacts the structure reconstruction results. In this paper, a comparison study of the aforementioned algorithms is conducted to identify the most suitable algorithm, in terms of accuracy and reliability, for reconstructing civil infrastructure. The free variables tested are baseline, depth, and motion. A concrete girder bridge was selected as the "test-bed" to reconstruct using an off-the-shelf camera capturing imagery from all possible positions that maximally the bridge's features and geometry. The feature points in the images were extracted and matched via the SURF descriptor. Finally, camera motions are estimated based on the corresponding image points by applying the aforementioned algorithms, and the results evaluated.

Maturity grids as tools for change management

One method to assess organizational capabilities is a maturity grid. MATURITY GRIDS AS TOOLS FOR CHANGE MANAGEMENT A maturity grid assessment is typically structured around a matrix or a grid. It consists of a series of cells where ...

集胞藻PCC6803中ORF sll0260对于维持基本生命活动的必要作用

集胞藻(Synechocystis sp.)6803的未知功能基因中有很多是细胞的基本生命活动所需要的,这些基因插入失活往往会导致细胞死亡,因而得不到分离完全的突变株,难以进行遗传学研究。构建突变株以铜离子调控的启动子PpetE来控制此类未知功能基因的表达则可能获得完全分离。构建PpetE-sll0260突变株并对sll0260必要作用进行研究。在完全分离的突变株中,去除铜离子可关闭sll0260的表达。此时,突变株生长受到严重抑制,色素含量大为降低,类囊体膜结构破坏,光合作用消失,呼吸能力下降。这些结果

红色伪角毛虫的形态学重描述及与相近种的比较(纤毛门,腹毛目)

利用活体观察、蛋白银染色技术对1种海水腹毛目纤毛虫—红色伪角毛虫Pseudokeronopsis rubra的青岛种群之活体形态和纤毛图式做了研究。其特征如下:虫体呈长带状,尾钝圆,身体柔软,高度可曲;皮层颗粒棕黄色,主要呈玫瑰花形分布,其余散布;表膜下具另1种无色、双面凹形颗粒。口围带小膜数为48～55;左、右缘棘毛各1列,中腹棘毛排成典型的锯齿状并延伸至横棘毛附近;额棘毛无明确分化,呈冠状排布并与中腹棘毛列相连续;口棘毛1根,额前棘毛2根;背触毛4列。大核90～140枚。伸缩泡位于体后左侧1/3处。经

Boundary effects on the vibration statistics of a random plate

This paper considers the estimation of statistics of displacement of a vibrating rectangular plate with random wave scatterers. The influence of uncertainty is investigated using point impedance theory. Coherent boundary effects are seen, which decrease when the number of scatterers increases. The boundary effect is investigated using images and the first side and corner reflections are found to be a minimum requirement to estimate the spatial correlation. Statistics for point driven response are investigated under the assumption that the statistics of the natural frequencies follow those of the Gaussian Orthogonal Ensemble (GOE). The estimates are compared with Monte Carlo simulation results, and they show good agreement. © 2012 Elsevier Ltd. All rights reserved.

念珠藻葛仙米生理生化特性对不同低温胁迫的响应

研究了不同培养温度下对念珠藻葛仙米的生长和相关生理生化特性的变化。结果表明,低温抑制葛仙米的生长,在2℃~5℃低温下其生长甚至完全停止;在10℃低温胁迫下,其生长延滞期变长,其后仍能保持正常生长。低温胁迫下,葛仙米光合系统II(PSII)的光合效率(Fv/Fm)的变化趋势与生长曲线相似;细胞电解质渗透率在低温胁迫初期尚能保持比较低的水平,但随着时间延长而升高;可溶性糖和还原性糖含量的变化则随胁迫加剧有不同程度升高。可溶性蛋白含量则在低温下保持比较低的水平。这些结果表明,低温对葛仙米的生长和光合作用具有抑制

集胞藻PCC6803 priA基因的突变体

中国科学院知识创新工程重要方向项目(KSCX2-SW-332)

Bayesian non-parametrics and the probabilistic approach to modelling.

Modelling is fundamental to many fields of science and engineering. A model can be thought of as a representation of possible data one could predict from a system. The probabilistic approach to modelling uses probability theory to express all aspects of uncertainty in the model. The probabilistic approach is synonymous with Bayesian modelling, which simply uses the rules of probability theory in order to make predictions, compare alternative models, and learn model parameters and structure from data. This simple and elegant framework is most powerful when coupled with flexible probabilistic models. Flexibility is achieved through the use of Bayesian non-parametrics. This article provides an overview of probabilistic modelling and an accessible survey of some of the main tools in Bayesian non-parametrics. The survey covers the use of Bayesian non-parametrics for modelling unknown functions, density estimation, clustering, time-series modelling, and representing sparsity, hierarchies, and covariance structure. More specifically, it gives brief non-technical overviews of Gaussian processes, Dirichlet processes, infinite hidden Markov models, Indian buffet processes, Kingman's coalescent, Dirichlet diffusion trees and Wishart processes.