A Survey on Monocular Re-Localization: From the Perspective of Scene Map Representation

Monocular Re-Localization (MRL) is a critical component in autonomous applications, estimating 6 degree-of-freedom ego poses w.r.t. the scene map based on monocular images. In recent decades, significant progress has been made in the development of MRL techniques. Numerous algorithms have accomplished extraordinary success in terms of localization accuracy and robustness. In MRL, scene maps are represented in various forms, and they determine how MRL methods work and how MRL methods perform. However, to the best of our knowledge, existing surveys do not provide systematic reviews about the relationship between MRL solutions and their used scene map representation. This survey fills the gap by comprehensively reviewing MRL methods from such a perspective, promoting further research. 1) We commence by delving into the problem definition of MRL, exploring current challenges, and comparing ours with existing surveys. 2) Many well-known MRL methods are categorized and reviewed into five classes according to the representation forms of utilized map, i.e., geo-tagged frames, visual landmarks, point clouds, vectorized semantic map, and neural network-based map. 3) To quantitatively and fairly compare MRL methods with various map, we introduce some public datasets and provide the performances of some state-of-the-art MRL methods. The strengths and weakness of MRL methods with different map are analyzed. 4) We finally introduce some topics of interest in this field and give personal opinions. This survey can serve as a valuable referenced materials for MRL, and a continuously updated summary of this survey is publicly available to the community at: https://github.com/jinyummiao/map-in-mono-reloc.Comment: 33 pages, 10 tables, 16 figures, under revie

Abstract Enhancing Database Correctness: A Statistical Approach

In this paper, we introduce a new type of integrity con-straint, which we call a statistical constraint, and discuss its applicability to enhancing database correctness. Sta-tistical constraints manifest embedded relationships among current attribute values in the database and are characterized by their probabilistic nature. They can be used to detect potential errors not easily detected by the conventional constraints. Methods for extracting statisti-cal constraints from a relation and enforcement of such constraints are described. Preliminary performance eval-uation of enforcing statistical constraints on a real life database is also presented. 1

Effectiveness of Singapore's pro-family policies in 2004.

This report discusses the possible reasons behind the declining birthrate despite the policies implemented over the years. We investigate the effectiveness of these policies, focusing on new and enhanced pro-family policies introduced in August 2004

Statistical Inference of Unknown Attribute Values In

In this paper, we propose to use statistical methods to estimate unknown attribute values in databases, as com-pared to assigning possible values at users ’ discretion in common practice. Regression models and classification analysis are introduced for estimating continuous and categorical unknown attribute values, respectively. Pro-cedures for selecting relevant attributes in a relation and preliminary experimental results of the proposed mod-els on a real life database are also presented

A Unified Multiple-Target Positioning Framework for Intelligent Connected Vehicles

Future intelligent transport systems depend on the accurate positioning of multiple targets in the road scene, including vehicles and all other moving or static elements. The existing self-positioning capability of individual vehicles remains insufficient. Also, bottlenecks in developing on-board perception systems stymie further improvements in the precision and integrity of positioning targets. Vehicle-to-everything (V2X) communication, which is fast becoming a standard component of intelligent and connected vehicles, renders new sources of information such as dynamically updated high-definition (HD) maps accessible. In this paper, we propose a unified theoretical framework for multiple-target positioning by fusing multi-source heterogeneous information from the on-board sensors and V2X technology of vehicles. Numerical and theoretical studies are conducted to evaluate the performance of the framework proposed. With a low-cost global navigation satellite system (GNSS) coupled with an initial navigation system (INS), on-board sensors, and a normally equipped HD map, the precision of multiple-target positioning attained can meet the requirements of high-level automated vehicles. Meanwhile, the integrity of target sensing is significantly improved by the sharing of sensor information and exploitation of map data. Furthermore, our framework is more adaptable to traffic scenarios when compared with state-of-the-art techniques

Monocular Localization with Vector HD Map (MLVHM): A Low-Cost Method for Commercial IVs

Real-time vehicle localization (i.e., position and orientation estimation in the world coordinate system) with high accuracy is the fundamental function of an intelligent vehicle (IV) system. In the process of commercialization of IVs, many car manufacturers attempt to avoid high-cost sensor systems (e.g., RTK GNSS and LiDAR) in favor of low-cost optical sensors such as cameras. The same cost-saving strategy also gives rise to an increasing number of vehicles equipped with High Definition (HD) maps. Rooted upon these existing technologies, this article presents the concept of Monocular Localization with Vector HD Map (MLVHM), a novel camera-based map-matching method that efficiently aligns semantic-level geometric features in-camera acquired frames against the vector HD map in order to achieve high-precision vehicle absolute localization with minimal cost. The semantic features are delicately chosen for the ease of map vector alignment as well as for the resiliency against occlusion and fluctuation in illumination. The effective data association method in MLVHM serves as the basis for the camera position estimation by minimizing feature re-projection errors, and the frame-to-frame motion fusion is further introduced for reliable localization results. Experiments have shown that MLVHM can achieve high-precision vehicle localization with an RMSE of 24 cm with no cumulative error. In addition, we use low-cost on-board sensors and light-weight HD maps to achieve or even exceed the accuracy of existing map-matching algorithms

Prophylactic Percutaneous Kyphoplasty Treatment for Nonfractured Vertebral Bodies in Thoracolumbar for Osteoporotic Patients

Purpose. The occurrence of new vertebral compression fractures (VCFs) is a common complication after percutaneous kyphoplasty (PKP). Secondary VCFs after PKP occur predominantly in the thoracolumbar segment (T11 to L2). Prophylactic injections of cement into vertebral bodies in order to reduce new VCFs have rarely been reported. The main purpose of this study was to investigate whether prophylactically injecting cement into a nonfractured vertebral body at the thoracolumbar level (T11-L2) could reduce the occurrence of new VCFs. Methods. From July 2011 to July 2018, PKP was performed in 86 consecutive patients with osteoporotic vertebral compression fractures (OVCFs) in the thoracolumbar region (T11-L2). All patients selected underwent PKP because of existing OVCFs (nonprophylactic group). Additionally, 78 consecutive patients with fractured vertebrae in the thoracolumbar region (T11-L2) with OVCFs underwent PKP and received prophylactic injections of cement into their nonfractured vertebrae in the thoracolumbar region (T11-L2) (prophylactic group). The visual analog scale (VAS) scores and incidence of new VCFs after PKP were compared between the two groups. Results. The mean VAS scores improved from 8.00±0.79 preoperatively to 1.62±0.56 at the last follow-up in the nonprophylactic group and improved from 8.17±0.84 to 1.76±0.34 in the prophylactic group (P>0.05). In the nonprophylactic group, 21 of 86 patients (24.4%) developed new VCFs within one year after PKP, of whom 15 patients (71.4%) developed VCFs within 3 months. In the prophylactic group, 8 of 78 patients (10.3%) developed new VCFs within one year, and 6 of these 8 patients (75%) developed new VCFs within 3 months. The incidence of new VCFs was significantly higher in the nonprophylactic group than that in the prophylactic group at one year (P=0.018), but there were no statistically significant differences at three months (P=0.847). Conclusions. Prophylactic injections of cement into nonfractured (T11-L2) vertebral bodies reduced the incidence of secondary VCFs after PKP in patients with OVCFs, but there was no significant difference in local back pain (VAS) scores between the two groups