利用信息融合方法的三维特征提取

本文提出了一种基于信息融合的物体三维特征的提取方法，该方法利用两幅互相配准的三维测距图像和灰度图像，来提取多面体的三维特征。首先，通过分析灰度图像中的灰度变化及测距图像中的测距值变化，分别求取各自图像中物体的特征点及特征边；然后，利用两配准图像之间的对应关系，求得所有特征点、面与多边形在三维测距图像中的三维表示；接着，通过分析三维测距图像中所测得的各候选平面上特定点与边处的曲率及法向，验证候选平面     

Rectilinear steiner tree heuristics and minimum spanning tree algorithms using geographic nearest neighbors

We study the application of the geographic nearest neighbor approach to two problems. The first problem is the construction of an approximately minimum length rectilinear Steiner tree for a set ofn points in the plane. For this problem, we introduce a variation of a subgraph of sizeO(n) used by YaO [31] for constructing minimum spanning trees. Using this subgraph, we improve the running times of the heuristics discussed by Bern [6] fromO(n ² log n) toO(n log² n). The second problem is the construction of a rectilinear minimum spanning tree for a set ofn noncrossing line segments in the plane. We present an optimalO(n logn) algorithm for this problem. The rectilinear minimum spanning tree for a set of points can thus be computed optimally without using the Voronoi diagram. This algorithm can also be extended to obtain a rectilinear minimum spanning tree for a set of nonintersecting simple polygons.The results in this paper are a part of Y. C. Yee's Ph.D. thesis done at SUNY at Albany. He was supported in part by NSF Grants IRI-8703430 and CCR-8805782. S. S. Ravi was supported in part by NSF Grants DCI-86-03318 and CCR-89-05296.     

基于RD算法的星载SAR斜视成像

本文研究了用距离一多普勒（ＲＤ）算法来实现星载 ＳＡＲ的斜视成像处理。给出了星载 ＳＡＲ斜视时的空间几何模型和回波信号模型，详细分析了地球自转和斜视产生的多普勒质心所引起的距离走动差异，及时域和频域校正对成像的影响，并研究了一种改进的ＲＤ算法进行距离走动的校正，此算法能适应大的斜视距离走动和地球自转距离走动。针对不同的距离走动校正进行了计算机仿真，理论分析和仿真结果表明：这种改进的ＲＤ算法是有效的。     

Algorithm for finding all k nearest neighbors

A very simple algorithm for computing all k nearest neighbors in 2-D is presented. The method does not rely on complicated forms of tessellation, it only requires simple data binning for fast range searching. Its applications range from scattered data interpolation to reverse engineering.     

基于距离信息扩展原理的物体识别方法

利用稀疏距离图象与灰度图象相结合，通过射影变换可使灰度图象特征有条件地获取距离信息，这称为 基于射影变换的距离信息扩展原理。利用这些距离信息可计算物体表面平面图形的欧氏空间不变量并对景物中的 物体产生假设。由于初始假设建立在可靠的基础上，并使用了带反馈的混合控制策略，使这种基于模型的物体识别 定位技术具有实用的前景。此文讨论了整个方法的原理及其实施方案，并实验验证了原理的正确性与有效性。     

应用烃类直接检测技术预测天然气藏

柴达木盆地位于青藏高原北部，是中国大型含油气盆地之一，历经４０年的勘探，发现了丰富的油气资源。柴达木盆地东部地区是第四纪沉降与沉积中心，区内第二系生储气岩厚度大、分布广、第四纪新构造运动形成的同生沉积构造发育、保存完整、具有形成大中型天然气田的地质条件。此外，由于该地区含气地层时代新、埋藏浅、成岩与胶结作用差、含气层厚度大、孔渗性好，加之构造条件简单，人文干扰小、是应用烃直接检测技术寻找天然气的有     

底排弹射击密集度的试验研究

底排弹底排装置的工作特性对底排弹的距离散布有着明显的影响。本文以初步的静态和飞行试验结果为依据,讨论了利用现有试验手段对底排因素引起的距离散布进行分析和计算的方法,并在此基础上提出了减小底排弹距离散布的途径。     

Coarse head pose estimation of construction equipment operators to formulate dynamic blind spots

Several hundred workers die in construction in the United States every year because equipment operators are unable to see their fellow workers during operation of their vehicle. In this paper we propose a step towards improving this situation by providing an automated method based on range imaging for estimating the coarse head orientation of a construction equipment operator. This research utilizes commercially-available low resolution range cameras to measure the continuously changing field-of-view (FOV) of an equipment operator in outdoor construction. This paper presents a methodology to measure so-called dynamic blind spot maps. The dynamic blind spot map is then projected on a known static equipment blind spot map that already exists to each construction vehicle. A robust computational coarse head pose estimation algorithm and results to three different pieces of construction equipment and multiple operators are presented. The developed method has the potential in automatically determining the spaces around vehicles that are currently not in the field-of-view of the vehicle operator thus providing eventually additional means and technology for improving safety in construction.     

Sediment storage and shallow groundwater response to beaver dam analogues in the Colorado Front Range,USA

Enthusiasm for using beaver dam analogues (BDAs) to restore incised channels and riparian corridors has been increasing. BDAs are expected to create a similar channel response to natural beaver dams by causing channel bed aggradation and overbank flow, which subsequently raise water tables and support vegetation growth. However, lack of funding for monitoring projects post‐restoration has limited research on whether BDAs actually cause expected channel change in the Front Range and elsewhere. Geomorphic and hydrologic response to BDAs was monitored in two watersheds 1 year post‐restoration. BDAs were studied at Fish Creek, a steep mountainous catchment, and Campbell Creek, a lower gradient piedmont catchment from May to October 2018. At each restoration site, the upstream‐ and downstream‐most BDAs were chosen for intensive study in comparison with unrestored reference reaches. Monitoring focused on quantifying sediment volumes in BDA ponds and recording changes to stream stage and riparian groundwater. Despite differences in physical basin characteristics, BDA pools at both sites stored similar volumes of sediment and stored more sediment than reference pools. Sediment storage is positively correlated to BDA height and pool surface area. However, BDAs did not have a significant influence on shallow groundwater. The lack of groundwater response proximal to BDAs could indicate that local watershed factors have a stronger influence on groundwater response than restoration design 1 year post‐restoration. Systematic, long‐term studies of channel and floodplain response to BDAs are needed to better understand how BDAs will influence geomorphology and hydrology.