View Planning Research Articles

Context Dependent Automatic View Planning: The Inspection of Mechanical Components

Computer-Aided Design and Applications is an international journal on the applications of CAD and CAM. It publishes papers in the general domain of CAD plus in emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, CAD data mining, CAD and the internet, CAD education, genetic algorithms and CAD engines. The journal is aimed at all developers and users of CAD technology to ptovide CAD solutions for various stages of design and manufacturing. The journal publishes all about Computer-Aided Design and Computer-Aided technologies.

Off-line view planning for the inspection of mechanical parts

3D optical scanning systems are used more and more for quality control purposes. The effective utilization of such systems needs an efficient virtual planning of the product acquisition viewpoints. Literature shows how 3D CAD product models can be used as reference in order to manage the verification process and as a basis for the computation of the optimal viewpoints. However, in the mechanical field, a variety of inspection tasks is experienced by engineers involved in the quality control process: GD&T verification, production phases control such as sheet metal cutting, evaluation of aesthetic appearance of parts, global shape deformation measurement and specific point deviations assessment. This leads to the necessity of flexible view planning approaches which adapt to the specificity of the required inspection task. The present work targets the development of a comprehensive view planning approach in which several algorithmic options are triggered by the product features to be inspected. Algorithms have been implemented in a prototypal software system which has been experimented as an off-line application to provide inputs to a multi-axis degree of freedom robot arm mounting an optical 3D scanner. Two test cases from die casting and automotive fields are presented. They show the computation of acquisition poses in a suitable sequence and efficiency in the obtained results.

View planning and mesh refinement effects on a semi-automatic three-dimensional photorealistic texture mapping procedure

A novel three-dimensional (3-D) photorealistic texturing process is presented that applies a view-planning and view-sequencing algorithm to the 3-D coarse model to determine a set of best viewing angles for capturing the individual real-world objects/building's images. The best sequence of views will generate sets of visible edges in each view to serve as a guide for camera field shots by either manual adjustment or equipment alignment. The best view tries to cover as many objects/building surfaces as possible in one shot. This will lead to a smaller total number of shots taken for a complete model reconstruction requiring texturing with photo-realistic effects. The direct linear transformation method (DLT) is used for reprojection of 3-D model vertices onto a two-dimensional (2-D) images plane for actual texture mapping. Given this method, the actual camera orientations do not have to be unique and can be set arbitrarily without heavy and expensive positioning equipment. We also present results of a study on the texture-mapping precision as a function of the level of visible mesh subdivision. In addition, the control points selection for the DLT method used for reprojection of 3-D model vertices onto 2-D textured images is also investigated for its effects on mapping precision. By using DLT and perspective projection theories on a coarse model feature points, this technique will allow accurate 3-D texture mapping of refined model meshes of real-world buildings. The novel integration flow of this research not only greatly reduces the human labor and intensive equipment requirements of traditional methods, but also generates a more appealing photo-realistic appearance of reconstructed models, which is useful in many multimedia applications.

A new method for efficient three‐dimensional reconstruction of outdoor environments using mobile robots

AbstractIn this paper, a method for robotic exploration oriented to the automatic three‐dimensional (3D) reconstruction of outdoor scenes is presented. The proposed algorithm focuses on optimizing the exploration process by maximizing map quality, while reducing the number of scans required to create a good‐quality 3D model of the environment. This is done by using expected information gain, expected model quality, and trajectory cost estimation as criteria for view planning. The method has been tested with an all‐terrain mobile robot, which is also described in the paper. This robot is equipped with a SICK LMS 111 laser scanner attached to a spinning turret, which performs quick and complete all‐around scans. Different experiments of autonomous 3D exploration show the suitable performance of the proposed exploration algorithm. © 2011 Wiley Periodicals, Inc.

Geophysical analysis of the soils for civil (Geotechnical) engineering and urban planning purposes: Some case histories from Turkey

The aim of this study is to review the geophysical investigations in civil engineering and urban planning by some case histories in Turkey. Geophysics deals with a wide array of earth phenomena, including the temperature distribution of the earth's interior (the source, configuration and variations of the geomagnetic field) and the large-scale features of the terrestrial crust, such as rifts, continental sutures and mid-oceanic ridges. From the geophysical point of view, civil engineering and urban planning includes several geophysical topics used to investigate the physical properties, the physical techniques for regional and local land use planning or micro-zonation, the natural disaster risk estimation studies, etc. In this study, the geophysical approach, regarding civil engineering and urban planning against the natural or artificial disaster risk in macro (human/nature) and micro (society/earth) scales, is given. Geophysical methods provide solutions to a wide range of geotechnical problems: Slope stability, soil liquefaction and amplification studies, site investigations and testing, water works, subways, etc. In this study, an evaluation of the geophysical methods applied to geotechnical problems related to the soils is presented. Soils consist of the products of physical and chemical weathering of the rocks of the earth’s crust. As a part of the engineering design, the aim of a site/soil investigation is to provide the basic data to evaluate the interaction of the natural environment with the proposed structure. As it is known, using physical measurements in geophysics, it is studied as the natural and artificially generated physical fields of the earth. Key words: Geotechnical engineering, geophysics, earthquake engineering, soils, soil dynamics.

Automatic LV localization and view planning for cardiac MRI acquisition

BackgroundLocalization of the heart is typically performed using amulti-step approach involving the acquisition of double-oblique localizer images. Based on the localizers thestandard heart views are planned. This approach isoperator-dependent and time consuming.ObjectiveTo demonstrate feasibility of a fully automatic and fastapproach to heart localization and slice prescriptionfrom a highly-accelerated, single breath-hold 3D acquisi-tion through a machine learning method.MethodsA 3D full-chest MR scan is obtained through parallelimaging within a single breath-hold. A single volume isacquired at mid-diastole using an ECG gated segmentedacquisition with T2-prepared SSFP readout with chemi-cal shift fat suppression. Typical protocol parametersare: 400x400x220 mm

Integrated Assessment System of Sustainable Communities using BIM Technology

Utilizing the concepts of sustainability in urban community design, the elements of the physical spatial design – such as building stock lay–out, building form including envelope design, and landscape design – are strongly considered to integrate with the issues of the urban landscape view planning and the environmental planning – such as energy efficiency, sunshine access, CO2 emissions and absorptions, natural ventilation, and urban heat island phenomena. While high-rise apartment style has dominated most of urban community design as physical patterns of spatial design widely ranging from new towns to urban redevelopments in Korea, basic design evaluation tools hardly have been developed yet. Also, there is no specialized assessment system focused on urban community design. Therefore, the purpose of this research was to develop an integrated design evaluation tool focused on the basic design phase for urban community development, named ‘SUSB–UC for Basic Design’. It was a part of an integrated framework...

Measurement quality metrics for rapid laser range scanning

Quality metrics quantify by how much some aspect of a measurement deviates from a predefined standard. Measurement quality evaluations of laser range scanner data are used to perform range image registration, merging measurements, and view planning. We develop a scanning method that uses laser range scanner quality metrics to both reduce the time required to obtain a complete range image from a single viewpoint and the number of measurements obtained during the scanning process. This approach requires a laser range scanner capable of varying both the area and sampling density of individual scans, but can be combined with view planning methods to reduce the total time required to obtain a complete surface map of an object. Several new quality metrics are introduced: outlier, resolvability, planarity, integration, return, and enclosed quality metrics. These metrics are used as part of a quality-based merge method, referred to here as a quality-weighted modified Kalman minimum variance (weighted-MKMV) estimation method. Experimental evidence is presented confirming that this approach can significantly reduce the total scanning time. This approach could be particularly useful for rapidly generating CAD models of real-world objects.

View planning and automated data acquisition for three‐dimensional modeling of complex sites

AbstractConstructing highly detailed three‐dimensional (3‐D) models of large complex sites using range scanners can be a time‐consuming manual process. One of the main drawbacks is determining where to place the scanner to obtain complete coverage of a site. We have developed a system for automatic view planning called VuePlan. When combined with our mobile robot, AVENUE, we have a system that is capable of modeling large‐scale environments with minimal human intervention throughout both the planning and acquisition phases. The system proceeds in two distinct stages. In the initial phase, the system is given a two‐dimensional site footprint with which it plans a minimal set of sufficient and properly constrained covering views. We then use a 3‐D laser scanner to take scans at each of these views. When this planning system is combined with our mobile robot it automatically computes and executes a tour of these viewing locations and acquires them with the robot's onboard laser scanner. These initial scans serve as an approximate 3‐D model of the site. The planning software then enters a second phase in which it updates this model by using a voxel‐based occupancy procedure to plan the next best view (NBV). This NBV is acquired, and further NBVs are sequentially computed and acquired until an accurate and complete 3‐D model is obtained. A simulator tool that we developed has allowed us to test our entire view planning algorithm on simulated sites. We have also successfully used our two‐phase system to construct precise 3‐D models of real‐world sites located in New York City: Uris Hall on the campus of Columbia University and Fort Jay on Governors Island. © 2009 Wiley Periodicals, Inc.

Model-based view planning

This paper presents a multi-phase, model-based approach to view planning for automated, high fidelity object inspection or reconstruction by means of laser scanning range sensors. We describe the critical phase, fine modeling, in detail. Quality objectives and performance measures are defined. Camera and positioning system performance is modeled statistically. A theoretical framework is presented. The method is applicable to a broad class of objects with reasonable geometry and reflectance properties. Sampling of object surface and viewpoint space is characterized, including measurement and pose errors. The technique is generalizable for common range cameras and positioning systems.

Extending the Path-Planning Horizon

The mobility sensors on a typical mobile robot vehicle have limited range. Therefore a navigation system has no knowledge about the world beyond this sensing horizon. As a result, path planners that rely only on this knowledge to compute paths are unable to anticipate obstacles sufficiently early and have no choice but to resort to an inefficient local obstacle avoidance behavior. To alleviate this problem, we present an opportunistic navigation and view planning strategy that incorporates look-ahead sensing of possible obstacle configurations. This planning strategy is based on a “what-if” analysis of hypothetical future configurations of the environment. Candidate sensing positions are evaluated based on their ability to observe anticipated obstacles. These sensing positions identified by this forward-simulation framework are used by the planner as intermediate waypoints. The validity of the strategy is supported by results from simulations as well as field experiments with a real robotic platform. These results show that significant reduction in path length can be achieved by using this framework.

多スタート局所探索法を用いた多数人物追跡のための複数能動カメラの同時視線プランニング

多スタート局所探索法を用いた多数人物追跡のための複数能動カメラの同時視線プランニング

Integration of view planning with nonuniform surface sampling techniques for three-dimensional object inspection

Optimizing view planning achieves the goal of minimum occlusion and minimum rotation to insure complete inspection of an object, and not only satisfies the goal of view planning, but also automatically maximizes the number of surfaces to which adaptive sampling can most fully be applied. The best view based on visible edge length can usually not only minimize the number of rotations needed to inspect an entire object, but can also provide the maximum amount of information for integration with nonuniform sampling techniques for a variety of parts and manufacturing processes. This new integration approach of first viewing then sampling establishes that the optimization criterion of maximum edge length is more robust than anticipated in its original role for view planning alone. The best view based on the number of visible faces and the face area has proven applicable to integrating the finite element (FEM) centroid sampling and indirect adaptive sampling techniques, respectively, for the inspection of sculptured surface products. Experimental work has verified various theories proposed. The verified view planning criteria include both the edge length and the number of visible faces criterion. Of them, the number of visible faces criterion not only maximizes the number of visible meshes for centroid sampling, but also reveals the maximum amount of high curvature regions of an object.

2A1-C17 複数人物の追跡のための複数カメラの視線プランニング

This paper describes a view planning of multiple cameras for tracking multiple persons. View planning of cameras is a very important problem in watching multiple persons in a large room by using a few cameras. We select the focuses of attention (FOAs) of cameras efficiently by predicting persons' future positions with their uncertainty. First, we propose an exhaustive search-based planning method and a multi-start local search-based method for tracking persons continuously and compare them. In these methods, we set the FOAs of cameras on the positions so that cameras can catch as many persons as possible. Next, we propose a multi-start local search method for tracking persons intermittently and compare this view planning with others based on a differnt evaluation criterion which allows frequent shifts of the FOAs of cameras. This view planning outperforms the others and is considered to be appropriate for wide area surveillance systems.

Automatic view planning with self-termination in 3D object reconstructions

Viewpoint planning plays an important role in automatic 3D model reconstruction. The objective of view planning in a visual sensing system is to make task-directed decisions for optimal sensing pose selection. In this paper we present a method of view planning for automatically constructing the model of an unknown object from range images. The method computes the next best view in two steps. First, the exploration direction for the next view is determined via a mass vector chain (MVC) based scheme. Then the accurate position of the next view is obtained by computing the boundary integral of the vectors fields. The position with the maximum integral value is selected as the next best view (NBV). We also present a self-termination criterion for judging the completion condition in the measurement and reconstruction process. The termination condition is derived based on changes in the volume computed from two successive viewpoints. The experimental results show that the method is effective in practical implementation.

Recognizing Large Isolated 3-D Objects Through Next View Planning Using Inner Camera Invariants

Most model-based three-dimensional (3-D) object recognition systems use information from a single view of an object. However, a single view may not contain sufficient features to recognize it unambiguously. Further, two objects may have all views in common with respect to a given feature set, and may be distinguished only through a sequence of views. A further complication arises when in an image, we do not have a complete view of an object. This paper presents a new online scheme for the recognition and pose estimation of a large isolated 3-D object, which may not entirely fit in a camera's field of view. We consider an uncalibrated projective camera, and consider the case when the internal parameters of the camera may be varied either unintentionally, or on purpose. The scheme uses a probabilistic reasoning framework for recognition and next-view planning. We show results of successful recognition and pose estimation even in cases of a high degree of interpretation ambiguity associated with the initial view.

Keeping smart, omnidirectional eyes on you

An adaptive panoramic stereo approach for two cooperative mobile platform is presented. There are four key features in the approach: 1) omnidirectional stereovision with an appropriate vertical FOV, and a simple camera calibration method; 2) cooperative mobile platforms for mutual dynamic calibration and best view planning; 3) 3D matching after meaningful object (human subject) extraction; and 4) real-time performance. The integration of omnidirectional vision with mutual awareness and dynamic calibration strategies allows intelligent cooperation between visual agents. This provides an effective way to solve the problems of limited resources, view planning, occlusion, and motion detection of movable robotic platforms. Experiments have shown that this approach is quite promising.

Dynamic mutual calibration and view planning for cooperative mobile robots with panoramic virtual stereo vision

This paper presents a panoramic virtual stereo vision approach to the problem of detecting and localizing multiple moving objects (e.g., humans) in an indoor scene. Two panoramic cameras, residing on different mobile platforms, compose a virtual stereo sensor with a flexible baseline. A novel “mutual calibration” algorithm is proposed, where panoramic cameras on two cooperative moving platforms are dynamically calibrated by looking at each other. A detailed numerical analysis of the error characteristics of the panoramic virtual stereo vision (mutual calibration error, stereo matching error, and triangulation error) is given to derive rules for optimal view planning. Experimental results are discussed for detecting and localizing multiple humans in motion using two cooperative robot platforms.

Active recognition through next view planning: a survey

3-D object recognition involves using image-computable features to identify 3-D object. A single view of a 3-D object may not contain sufficient features to recognize it unambiguously. One needs to plan different views around the given object in order to recognize it. Such a task involves an active sensor—one whose parameters (external and/or internal) can be changed in a purposive manner. In this paper, we review two important applications of an active sensor. We first survey important approaches to active 3-D object recognition. Next, we review existing approaches towards another important application of an active sensor namely, that of scene analysis and interpretation.

View planning for automated three-dimensional object reconstruction and inspection

Laser scanning range sensors are widely used for high-precision, high-density three-dimensional (3D) reconstruction and inspection of the surface of physical objects. The process typically involves planning a set of views, physically altering the relative object-sensor pose, taking scans, registering the acquired geometric data in a common coordinate frame of reference, and finally integrating range images into a nonredundant model. Efficiencies could be achieved by automating or semiautomating this process. While challenges remain, there are adequate solutions to semiautomate the scan-register-integrate tasks. On the other hand, view planning remains an open problem---that is, the task of finding a suitably small set of sensor poses and configurations for specified reconstruction or inspection goals. This paper surveys and compares view planning techniques for automated 3D object reconstruction and inspection by means of active, triangulation-based range sensors.