Novel Compression Algorithm Based on Sparse Sampling of 3-D Laser Range Scans

Cataloged from PDF version of article.Three-dimensional models of environments can be very useful and are commonly employed in areas such as robotics, art and architecture, facility management, water management, environmental/industrial/urban planning and documentation. A 3-D model is typically composed of a large number of measurements. When 3-D models of environments need to be transmitted or stored, they should be compressed efficiently to use the capacity of the communication channel or the storage medium effectively. We propose a novel compression technique based on compressive sampling applied to sparse representations of 3-D laser range measurements. The main issue here is finding highly sparse representations of the range measurements, since they do not have such representations in common domains, such as the frequency domain. To solve this problem, we develop a new algorithm to generate sparse innovations between consecutive range measurements acquired while the sensor moves. We compare the sparsity of our innovations with others generated by estimation and filtering. Furthermore, we compare the compression performance of our lossy compression method with widely used lossless and lossy compression techniques. The proposed method offers a small compression ratio and provides a reasonable compromise between the reconstruction error and processing time

A compression method based on compressive sampling for 3-D laser range scans of indoor environments

When 3-D models of environments need to be transmitted or stored, they should be compressed efficiently to increase the capacity of the communication channel or the storage medium. We propose a novel compression technique based on compressive sensing, applied to sparse representations of 3-D range measurements. We develop a novel algorithm to generate sparse innovations between consecutive range measurements along the axis of the sensor's motion, since the range measurements do not have highly sparse representations in common domains. Compared with the performances of widely used compression techniques, the proposed method offers the smallest compression ratio and provides a reasonable balance between reconstruction error and processing time. © 2011 Springer Science+Business Media B.V

A novel compression algorithm based on sparse sampling of 3-D laser range scans

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 68-75.3-D models of environments can be very useful and are commonly employed in areas such as robotics, art and architecture, environmental planning and documentation. A 3-D model is typically comprised of a large number of measurements. When 3-D models of environments need to be transmitted or stored, they should be compressed efficiently to use the capacity of the communication channel or the storage medium effectively. In this thesis, we propose a novel compression technique based on compressive sampling, applied to sparse representations of 3-D laser range measurements. The main issue here is finding highly sparse representations of the range measurements, since they do not have such representations in common domains, such as the frequency domain. To solve this problem, we develop a new algorithm to generate sparse innovations between consecutive range measurements acquired while the sensor moves. We compare the sparsity of our innovations with others generated by estimation and filtering. Furthermore, we compare the compression performance of our lossy compression method with widely used lossless and lossy compression techniques. The proposed method offers small compression ratio and provides a reasonable compromise between reconstruction error and processing time.Dobrucalı, OğuzcanM.S

A comparative study between wmms and tls for the stability analysis of the San Pedro church barrel vault by means of the finite element method

Stability of masonry constructions is highly conditioned by the geometric disposition of its elements due to its low tensile strength and great compressive mechanical properties. Under this framework, this paper attempts to evaluate the suitability of a wearable mobile mapping solution, equipped in a backpack and based on the well-known simultaneous location and mapping paradigm, for the structural diagnosis of historical constructions. To evaluate the suitability of this device, the structural analysis obtained is compared with a high precision terrestrial laser scanner, which is considered as ground truth. The Romanesque church of San Pedro (Becerril del Carpio, Spain) was selected as a study case. This construction, initially conceived in the XIIIth century, has experimented in the past a soil settlement promoting the leaning of the north wall, several plastic hinges in its barrel vault and a visible geometrical deformation. The comparison of both techniques was carried out at different levels: i) an evaluation of the time needed to obtain the point cloud of the church; ii) an accuracy assessment based on the comparison of a terrestrial network using artificial spheres as checkpoints and; iii) an evaluation of the discrepancies, in terms of safety factor and collapse topology, found during the advance numerical evaluation of the barrel vault by means of the finite element method. This comparison places this wearable mobile mapping solution as an interesting tool for the creation of advanced numerical simulations to evaluate the structural stability of historical constructionsJunta de Castilla y León | Ref. SA075P17FEDER | Ref. SOE1/P5/P025

A review of laser scanning for geological and geotechnical applications in underground mining

Laser scanning can provide timely assessments of mine sites despite adverse challenges in the operational environment. Although there are several published articles on laser scanning, there is a need to review them in the context of underground mining applications. To this end, a holistic review of laser scanning is presented including progress in 3D scanning systems, data capture/processing techniques and primary applications in underground mines. Laser scanning technology has advanced significantly in terms of mobility and mapping, but there are constraints in coherent and consistent data collection at certain mines due to feature deficiency, dynamics, and environmental influences such as dust and water. Studies suggest that laser scanning has matured over the years for change detection, clearance measurements and structure mapping applications. However, there is scope for improvements in lithology identification, surface parameter measurements, logistic tracking and autonomous navigation. Laser scanning has the potential to provide real-time solutions but the lack of infrastructure in underground mines for data transfer, geodetic networking and processing capacity remain limiting factors. Nevertheless, laser scanners are becoming an integral part of mine automation thanks to their affordability, accuracy and mobility, which should support their widespread usage in years to come

듀얼미러 라이다 이미징을 위한 타이밍이 고려된 샘플링 알고리즘

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2019. 2. Lee, Hyuk-Jae.In recent years, active sensor technologies such as light detection and ranging (LIDAR) have been intensively studied in theory and widely adopted in many applications, i.e., self-driving cars, robotics and sensing. Generally, the spatial resolution of a depth-acquisition device, such as a LiDAR sensor, is limited because of a slow acquisition speed. To accurately reconstruct a depth image from a limited spatial resolution, a two-stage sampling process has been widely used. However, two-stage sampling uses an irregular sampling pattern for the sampling operation, which requires a large amount of computation for reconstruction. A mathematical formulation of a LiDAR system demonstrates that the existing two-stage sampling does not satisfy its timing constraint for practical use. Therefore, designing a LiDAR system with an efficient sampling algorithm is a significant technological challenge. Firstly, this thesis addresses the problem of adopting the state-of-art laser marking system of a dual-mirror deflection scanner when creating a high-definition LIDAR system. Galvanometer scanners are modeled and parameterized based on concepts of their controllers and the well-known raster scanning method. The scanning strategy is then modeled and analyzed considering the physical scanning movement and the minimum spanning tree. From this analysis, the link between the quality of the captured image of a field of view (FOV) and the scanning speed is revealed. Furthermore, sufficient conditions are derived to indicate that the acquired image fully covers the FOV and that the captured objects are well aligned under a specific frame rate. Finally, a sample LIDAR system is developed to illustrate the proposed concepts. Secondly, to overcome the drawbacks of two-stage sampling, we propose a new sampling method that reduces the computational complexity and memory requirements by generating the optimal representatives of a sampling pattern in down-sample data. A sampling pattern is derived from a k-NN expanding operation from the downsampled representatives. The proposed algorithm is designed to preserve the object boundary by restricting the expansion-operation only to the object boundary or complex texture. In addition, the proposed algorithm runs in linear-time complexity and reduces the memory requirements using a down-sampling ratio. Experimental results with Middlebury datasets and Brown laser-range datasets are presented. Thirdly, state-of-the-art adaptive methods such as two-step sampling are highly effective while addressing indoor, less complex scenes at a moderately low sampling rate. However, their performance is relatively low in complex on-road environments, particularly when the sampling rate of the measuring equipment is low. To address this problem, this thesis proposes a region-of-interest-(ROI)-based sampling algorithm in on-road environments for autonomous driving. With the aid of fast and accurate road and object detection algorithms, particularly those based on convolutional neural networks (CNNs), the proposed sampling algorithm utilizes the semantic information and effectively distributes samples in road, object, and background areas. Experimental results with KITTI datasets are presented.최근 LIDAR (light detection and ranging)와 같은 능동적 센서 기술은 이론적으로도 집중적으로 연구되었고, 자율주행차, 로봇, 센싱 등 다양한 응용 분야에 널리 사용되고 있다. 일반적으로 LiDAR 센서와 같은 심도측정장치는 느린 속도 때문에 공간적 해상도가 제한된다. 제한된 공간적 해상도로부터 심도 이미지를 정확하게 재구성하기 위해서 2단계 샘플링 방법이 널리 사용되고 있다. 그러나 2단계 샘플링은 불규칙적인 샘플링 패턴으로 샘플링을 하기 때문에, 재구성 과정에 많은 양의 연산이 필요하다. LiDAR 시스템을 수학적인 모델을 사용하여 분석하였을 때, 기존의 2단계 샘플링은 실용적으로 사용되기 위한 타이밍 제약 조건을 만족하지 못함을 확인하였다. 따라서 효율적인 샘플링 알고리즘을 사용하는 LiDAR 시스템을 설계하는 것은 중요한 기술적 과제이다. 첫째, 본 논문은 최신의 레이저 마킹 시스템을 dual-mirror 스캐너에 적용하여 고해상도 LiDAR 시스템을 만드는 문제를 다룬다. Galvanometer 스캐너 컨트롤러와 잘 알려진 래스터 스캔 방법에 기초하여 Galvanometer 스캐너를 모델링, 매개변수화한다. 그리고 물리적인 스캐닝 움직임과 최소 신장 트리를 고려하여 스캐닝 방법을 모델링하고 분석한다. 분석으로부터 원하는 FOV (field of view)로 캡쳐된 이미지의 품질과 스캐닝 속도 사이의 관계를 밝혔다. 또한 획득된 이미지가 FOV를 완전히 표현하며, 캡쳐된 object들이 특정 프레임 레이트에서 잘 정렬됨을 나타내는 충분조건을 유도하였다. 마지막으로 제안된 개념을 확인하기 위해 샘플 LIDAR 시스템을 개발하였다. 둘째, 2단계 샘플링의 단점을 극복하기 위해, 다운 샘플 데이터에서 샘플링 패턴의 최적 표현을 생성함으로써 연산 복잡도와 메모리 요구량을 줄일 수 있는 새로운 샘플링 방법을 제안한다. 샘플링 패턴은 다운 샘플된 표현의 k-NN 확장 연산으로부터 도출된다. 제안된 방법은 물체 경계 또는 복잡한 텍스처에 한해서 확장연산을 수행함으로써 물체 경계를 보존하도록 설계되었다. 또한 제안하는 방법은 선형적인 시간 복잡도로 동작하며 다운 샘플링 비율을 이용하여 메모리 요구량을 줄인다. Middlebury 데이터셋과 Brown laser-range 데이터셋을 사용한 실험 결과가 제시된다. 셋째, 2단계 샘플링과 같은 최신의 적응적 방법들은 비교적 낮은 샘플링 레이트로 실내의 복잡하지 않은 장면들을 처리하는 데 매우 효과적이다. 그러나 복잡한 도로 환경에서는, 특히 측정 장비의 샘플링 레이트가 낮은 경우에, 해당 방법들의 성능이 상대적으로 떨어진다. 이 문제를 해결하기 위해 본 논문은 자율주행을 위한 도로 환경에서의 ROI (region-of-interest) 기반 샘플링 알고리즘을 제안한다. 제안된 샘플링 알고리즘은 CNN (convolutional neural network) 기반의 빠르고 정확한 도로 및 물체 감지 알고리즘을 사용하여, semantic 정보를 활용하고 도로, 물체, 배경 영역에 샘플들을 효과적으로 분배한다. KITTI 데이터셋을 사용한 실험 결과가 제시된다.Abstract i Table of Contents iii List of Figures vii List of Tables xi Chapter 1: Introduction １ 1.1. Overview １ 1.2. Scope and contributions ２ 1.3. Thesis Outlines ３ Chapter 2: Related work ４ 2.1. LiDAR sensors ４ 2.2. Sampling ６ 2.2.1. Sampling problem definition ６ 2.2.2. Sampling model ７ 2.2.3. Oracle Random sampling (Gradient-based sampling) ８ 2.3. Reconstruction ９ Chapter 3: Dual-Mirror LiDAR １１ 3.1. Introduction １１ 3.1.1. Related work １２ 3.2. Modelling a controller of dual-mirror scanners １３ 3.2.1. Dual-mirror scanners １３ 3.2.2. Controller Model １５ 3.2.2.1. FOV representation １５ 3.2.2.2. Timing constraints １６ 3.2.2.3. Maximum Speed of LiDAR scanners １７ 3.3. LiDAR scanning optimization problem １８ 3.3.1. Scanning Problem １９ 3.3.2. Optimal scanning pattern ２０ 3.3.2.1. Grid-graph representation of Field of View ２０ 3.3.2.2. Optimal scanning pattern ２１ 3.3.2.3. Combining an optimal sampling pattern with timing constraints ２4 3.4. LiDAR system Prototype ３０ 3.4.1. System overview ３０ 3.4.2. Speed evaluation ３２ 3.4.3. Subjective Evaluation ３３ 3.4.4. Accuracy Evaluation ３６ Chapter 4: Sampling for Dual-Mirror LiDAR: Sampling Model and Algorithm ３８ 4.1. Introduction ３８ 4.2. Sampling Model for Dual-Mirror LiDAR ４１ 4.2.1. Timing constraint ４１ 4.2.2. Memory-space constraint ４５ 4.2.3. New sampling problem with constraints ４７ 4.3. Proposed sampling Algorithm and Its Properties ４８ 4.3.1. Downsampling and k-NN expanding operator ４８ 4.3.2. Proposed Sampling Algorithm with k-NN Expanding ５２ 4.3.3. Example with Synthetic Data ５７ 4.3.4. Proposed sampling algorithm with interpolation ５９ 4.3.5. Timing and memory constraints ６２ 4.3.5.1. Timing constraint ６２ 4.3.5.2. Memory constraint ６３ 4.4. Experimental results ６４ 4.4.1. Comparison on the conventional sampling problem ６５ 4.4.1.1. Subjective comparison ６５ 4.4.1.2. Quantitative comparison ６５ 4.4.2. Comparison on the new sampling problem for LiDAR ６９ 4.4.2.1. Compression ratios ６９ 4.4.2.2. Quantitative evaluation with Peak-signal-to-noise-ratio ７０ 4.4.2.3. Quantitative evaluation with Percentages of bad pixels ７２ 4.4.3. Subjective evaluation ７７ 4.4.4. Proposed grid sampling and grid sampling method ７９ 4.4.4.1. Middlebury datasets ７９ 4.4.4.2. Brown Laser range datasets ８０ Chapter 5: ROI-based LiDAR Sampling in On-Road Environment for Autonomous Driving ８４ 5.1. Introduction ８４ 5.2. Proposed ROI-based sampling algorithm ８７ 5.2.1. Motivating example ８７ 5.2.2. ROI-based Sampling Problem ９１ 5.2.3. Proposed ROI-based sampling algorithm ９３ 5.2.4. Practical considerations ９４ 5.2.5. Distortion optimization problem ９５ 5.3. Experimental results ９６ 5.3.1. Datasets ９６ 5.3.2. Evaluation with different parameters ９９ 5.3.3. Object and quantitative comparisons １０２ Chapter 6: Implementation Issues １０８ 6.1. Implementation of gradient-based sampling １０８ 6.2. System overview １１１ Chapter 7: Conclusion １１３ References １１５ 초록 １２４Docto

LASER-SCANNER SURVEY OF STRUCTURAL DISORDERS: AN INSTRUMENT TO INSPECT THE HISTORY OF PARMA CATHEDRAL'S CENTRAL NAVE

This paper presents the use of laser scanner derived data for the study of the structural disorders in the central nave of the Parma Cathedral. An accurate three-dimensional model of the entire nave was realized to investigate deformations, in order to reconstruct the original conformation and the subsequent evolutions, also in comparison with previous surveys. Specifically, for the analysis presented in the paper, seven scans were performed, one for each bay: the results allowed to compare the deformations on the seven vaults, on the transverse and diagonal arches, giving first hints on the possible differences in the behaviour between the different elements. The measures on the levels of floor and pillars bases were analysed in a historical monitoring approach, in order to retrace the evolution of the differential settlements in time, since the construction of the building. Moreover, a structural analysis has been carried out on one transverse arch with distinct element analysis, with two different approaches. In one case, the structure was inserted exactly as surveyed, and then subjected to the actions. In the second case, the original geometry, before the deformation, was retraced through a parametric approach and the structural analysis basically started at the beginning of the building's life, thus trying to model not only the present structural situation, but also the path which led to the current deformation. The results were particularly meaningful as they showed that in the first case, disregarding the footsteps of history, the stress pattern inside the masonry was very different from the one obtained in the second case, which is more likely to represent the present conditions

3D Sensor Placement and Embedded Processing for People Detection in an Industrial Environment

Papers I, II and III are extracted from the dissertation and uploaded as separate documents to meet post-publication requirements for self-arciving of IEEE conference papers.At a time when autonomy is being introduced in more and more areas, computer vision plays a very important role. In an industrial environment, the ability to create a real-time virtual version of a volume of interest provides a broad range of possibilities, including safety-related systems such as vision based anti-collision and personnel tracking. In an offshore environment, where such systems are not common, the task is challenging due to rough weather and environmental conditions, but the result of introducing such safety systems could potentially be lifesaving, as personnel work close to heavy, huge, and often poorly instrumented moving machinery and equipment. This thesis presents research on important topics related to enabling computer vision systems in industrial and offshore environments, including a review of the most important technologies and methods. A prototype 3D sensor package is developed, consisting of different sensors and a powerful embedded computer. This, together with a novel, highly scalable point cloud compression and sensor fusion scheme allows to create a real-time 3D map of an industrial area. The question of where to place the sensor packages in an environment where occlusions are present is also investigated. The result is algorithms for automatic sensor placement optimisation, where the goal is to place sensors in such a way that maximises the volume of interest that is covered, with as few occluded zones as possible. The method also includes redundancy constraints where important sub-volumes can be defined to be viewed by more than one sensor. Lastly, a people detection scheme using a merged point cloud from six different sensor packages as input is developed. Using a combination of point cloud clustering, flattening and convolutional neural networks, the system successfully detects multiple people in an outdoor industrial environment, providing real-time 3D positions. The sensor packages and methods are tested and verified at the Industrial Robotics Lab at the University of Agder, and the people detection method is also tested in a relevant outdoor, industrial testing facility. The experiments and results are presented in the papers attached to this thesis.publishedVersio