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Speed Bump Detection Through Inertial Sensors and Deep Learning in a Multi-contextual Analysis

SN computer Science 2023年第1期4卷 18页

作者： Menegazzo, Jeferson von Wangenheim, Aldo Graduate Program in Computer Science (PPGCC) Image Processing and Computer Graphics Lab (LAPIX) Brazilian National Institute for Digital Convergence (INCoD) Department of Informatics and Statistics (INE) Federal University of Santa Catarina (UFSC)-Florianópolis Santa Catarina Brazil

Speed bumps are vertical raisings of the road pavement used to force drivers to slow down to ensure greater safety in traffic. However, these obstacles have disadvantages in terms of efficiency and safety, where the presence of speed bumps can affect travel time and fuel consumption, cause traffic jams, delay emergency vehicles, and cause vehicle damage or accidents when not properly signaled. Due to these factors, the availability of geolocation information for these obstacles can benefit several applications in Intelligent Transportation System (ITS), such as Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, allowing to trace more efficient routes or alert the driver of the presence of the obstacle ahead. Speed bump detection applications described in the literature employ cameras or inertial sensors, represented by accelerometers and gyroscopes. While camera-based solutions are mature with evaluation in different contextual conditions, those based on inertial sensors do not offer multi-contextual analyses, being mostly simple applications of proof of concept, not applicable in real-world scenarios. For this reason, in this work, we propose the development of a reliable speed bump detection model based on inertial sensors, capable of operating reliably in contextual variations: different vehicles, driving styles, and environments in which vehicles can travel to. For the model development and validation, we collect nine datasets with contextual variations, using three different vehicles, with three different drivers, in three different environments, in which there are three different surface types, in addition to variations in conservation state and the presence of obstacles and anomalies. The speed bumps are present in two different pavement types, asphalt and cobblestone. We use the collected data in experiments to evaluate aspects such as the influence of the placement of the sensors for vehicle data collection and the data window size. Afterwar

关键词： Autonomous vehicles Deep learning Inertial sensors Intelligent transport systems Road conditions Speed bump

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Digital Color Output Conformity to ISO12647-7 Standards (GRACoL 2013 [CGATS21-2-CRPC6]) With the Use of Statistical Process Control (SPC)

Journal of Technology, Management, and Applied Engineering

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Journal of Technology, Management, and Applied Engineering 2023年第4期39卷 1-18页

作者： Dharavath, Haji Naik Program Coordinator for the BS degree in Graphics Technology Department of Computer Electronics & Graphics Technology Central Connecticut State University New BritainCT06050 United States

The purpose of this applied research was to apply the statistical process control (SPC) to determine the digital color output conformity to ISO12647-7 standards in a color managed digital printing workflow (CMDPW) over a period of 100 days (N = 100). The quality of digital color printing is determined by these influential factors: screening method applied, type of printing process, calibration method, device profile, ink (dry toner or liquid toner), printer resolution, and the substrate (paper). For this research, only the color printing attribute overall average color deviation (ACD;ΔE(2000)) was analyzed to examine the CMDPW process consistency in a day-to-day digital printing operation. Printed colors from the random sample size (n= 80) were measured against the General Requirement for the Applications in the Commercial Offset Lithography (GRACoL 2013) standards to derive the colorimetric/ densitometric values. Reference colorimetric values used in the analysis were the threshold deviations (acceptable color deviations) as outlined in the ISO12647-7 standards (GRACoL 2013). A control chart analysis was applied for further determining the process (CMDPW) ACD variation. The data collected were run through multiple software applications (Microsoft Excel/SPSS/Minitab) to apply various statistical methods. Analyzed data from the experiment revealed that the printed colorimetric values were in match (aligned) with the GRACoL 2013 (reference/target) standards. Since the color values were in control throughout the process, this enabled the CMDPW to produce consistent acceptable color deviation (average printed ΔE(2000) = 2.978). (The acceptable threshold color deviation is ΔE(2000) ≤ 3.00.) © 2023 The Author(s). This is an open access article published under a Creative Commons Attribution 4.0 International License (https://***/licenses/by/4.0).

关键词： Colorimetry

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Exploring 3D Reconstruction with Drone Images: Advances and Challenges in Urban Environments 50

Exploring 3D Reconstruction with Drone Images: Advances and ...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Miranda Baldivieso, Thiago João da Silva Batista, Taise Grazielle Chagas, Fabio Suim Rodrigues Velho, Luiz Carlos Pacheco Ferreira Rosa, Paulo Fernando Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil State Institute of the Environment Inea RJ Rio de Janeiro Brazil Department of Science and Industry systems University of South-Eastern Norway Kongsberg Norway Department of Computer Graphics Institute for Pure and Applied Mathematics Rio de Janeiro Brazil Electrical Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9781665464543

This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, starting with image acquisition, followed by the application of specific photogrammetry software-both commercial and open-source-and concluding with a qualitative evaluation of the results. © 2024 IEEE.

关键词： Aerial photography

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Enhancing Performance of 3D Point Completion Network using Consistency Loss

arXiv

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arXiv 2024年

作者： Wijaya, Kevin Tirta Goenawan, Christofel Rio Kong, Seung-Hyun Computer Graphics Department Max Planck Institute for Informatics Saarbrücken66123 Germany Robotics Master Program KAIST Daejeon34051 Korea Republic of CCS Graduate School of Mobility KAIST Daejeon34051 Korea Republic of

Point cloud completion networks are conventionally trained to minimize the disparities between the completed point cloud and the ground-truth counterpart. However, an incomplete object-level point cloud can have multiple valid completion solutions when it is examined in isolation. This one-to-many mapping issue can cause contradictory supervision signals to the network because the loss function may produce different values for identical input-output pairs of the network. In many cases, this issue could adversely affect the network optimization process. In this work, we propose to enhance the conventional learning objective using a novel completion consistency loss to mitigate the one-to-many mapping problem. Specifically, the proposed consistency loss ensure that a point cloud completion network generates a coherent completion solution for incomplete objects originating from the same source point cloud. Experimental results across multiple well-established datasets and benchmarks demonstrated the proposed completion consistency loss have excellent capability to enhance the completion performance of various existing networks without any modification to the design of the networks. The proposed consistency loss enhances the performance of the point completion network without affecting the inference speed, thereby increasing the accuracy of point cloud completion. Notably, a state-of-the-art point completion network trained with the proposed consistency loss can achieve state-of-the-art accuracy on the challenging new MVP dataset. The code and result of experiment various point completion models using proposed consistency loss will be available at: https://***/kaist-avelab/ConsistencyLoss . © 2024, CC BY.

关键词： Cloud platforms

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Exploring 3D Reconstruction with Drone Images: Advances and Challenges in Urban Environments

Exploring 3D Reconstruction with Drone Images: Advances and ...

引用

Annual Conference of Industrial Electronics Society

作者： Thiago João Miranda Baldivieso Taise Grazielle Da Silva Batista Fabio Suim Chagas Luiz Carlos Pacheco Rodrigues Velho Paulo Fernando Ferreira Rosa Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil State Institute of the Environment Inea/RJ Rio de Janeiro Brazil Department of Science and Industry Systems University of South-Eastern Norway Kongsberg Norway Department of Computer Graphics Institute for Pure and Applied Mathematics Rio de Janeiro Brazil Electrical Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, starting with image acquisition, followed by the application of specific photogrammetry software—both commercial and open-source—and concluding with a qualitative evaluation of the results.

关键词： Industrial electronics Three-dimensional displays Urban areas Aircraft Image reconstruction Photogrammetry Drones

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computer graphics Challenges in Electron Microscope Tomography Visualization

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Microscopy and Microanalysis 2020年第S2期3卷 1127-1128页

作者： James W. Durkin Program of Computer Graphics Cornell University Ithaca NY14853

We are developing a collaborative research environment, the Collaboratory for Microscopic Digital Anatomy (CMDA), to provide remote access to the sophisticated instrumentation located at the Na-tional Center for Microscopy and Imaging Research (NCMIR). The project’s initial focus is the col-lection and analysis of data from NCMIR’s unique intermediate-high voltage transmission electron microscope (HVEM), an instrument expressly designed to obtain images from thick specimens con-taining substantial 3-D structure. Because of the electron optical characteristics of the microscope, its images represent a 2-D projection of the specimen’s 3-D structure. 3-D data is derived, using axial tomography, from a series of projections acquired as the specimen is successively tilted in small angu-lar increments. Visualizing the 3-D volume data generated by this procedure is a key challenge facing the project. Our experience suggests that existing visualization mechanisms are limited in their ability to fully access the data’s biologically interesting information.

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Vehicular Perception Based on Inertial Sensing: A Structured Mapping of Approaches and Methods

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SN computer Science 2020年第5期1卷 1-24页

作者： Menegazzo, Jeferson von Wangenheim, Aldo Graduate Program in Computer Science (PPGCC) Image Processing and Computer Graphics Lab (LAPIX) Department of Informatics and Statistics (INE) Brazilian Institute for Digital Convergence (INCoD) Federal University of Santa Catarina (UFSC) Santa Catarina Florianópolis Brazil

In this paper, we present a structured literature mapping of the state-of-the-art of vehicular perception methods and approaches using inertial sensors. An in-depth investigation and classification were performed employing the results of a systematic literature review. The analysis focused on identifying methods that capture signals provided by inertial sensors such as accelerometers and gyroscopes to recognize transient or persistent events associated with the vehicle’s movement. We classified these events into vehicular exteroception, associated with potholes, cracks, speed bumps, pavement type, conservation state;and vehicular proprioception, associated with lane change, braking, skidding, aquaplaning, turning right or left. Through the comprehensive study of publications in a 7-year time window, in addition to the methods, we have also identified their dependency factors, hardware platforms and applications. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Driver behaviour Driving style Inertial sensors Intelligent transport systems Road conditions Road surface anomaly

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Hybrid online autotuning for parallel ray tracing

Hybrid online autotuning for parallel ray tracing

引用

19th Eurographics Symposium on Parallel graphics and Visualization, EGPGV 2019

作者： Herveau, K. Pfaffe, P. Tillmann, M. Tichy, W.F. Dachsbacher, C. Computer Graphics Group Karlsruhe Institute of Technology Germany Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Germany

ISBN: (纸本)9783038680796

Acceleration structures are key to high performance parallel ray tracing. Maximizing performance requires configuring the degrees of freedom (e.g., construction parameters) these data structures expose. Whether a parameter setting is optimal depends on the input (e.g., the scene and view parameters) and hardware. Manual selection is tedious, error prone, and is not portable. To automate the parameter selection task we use a hybrid of model-based prediction and online autotuning. The combination benefits from the best of both worlds: One-shot configuration selection when inputs are known or similar, effective exploration of the configuration space otherwise. Online tuning additionally serves to train the model on real inputs without requiring a-priori training samples. Online autotuning outperforms best-practice configurations recommended by the literature, by up to 11% median. The model predictions achieve 95% of the online autotuning performance while reducing 90% of the autotuner overhead. Hybrid online autotuning thus enables always-on tuning of parallel ray tracing. © 2019 Eurographics Association. All rights reserved.

关键词： Ray tracing

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Multi-Contextual and Multi-Aspect Analysis for Road Surface Type Classification Through Inertial Sensors and Deep Learning

Multi-Contextual and Multi-Aspect Analysis for Road Surface ...

引用

Brazilian Symposium on Computing System Engineering (SBESC)

作者： Jeferson Menegazzo Aldo von Wangenheim Graduate Program in Computer Science (PPGCC) Image Processing and Computer Graphics Lab (LAPIX) Brazilian National Institute for Digital Convergence (INCoD) Federal University of Santa Catarina (UFSC) Florianópolis Brazil

ISBN: (数字)9781728182865

ISBN: (纸本)9781728182872

The demand for a variety of situational data from the traffic environment and its participants has intensified with the development of applications in Intelligent Transport Systems (ITS). Among these data, the road surface type classification is one of the most important and can be used in the entire ITS domain. For its widespread application, it is necessary to employ a robust technology for the generation of raw data and to develop of a reliable and stable model to process these data in order to produce the classification. The developed model must operate correctly in different vehicles, under different driving styles and in different environments in which a vehicle can travel. In this work we employ inertial sensors, represented by accelerometers and gyroscopes, which are a safe, non-polluting, and low-cost alternative, ideal for large-scale use. We collect nine datasets with contextual variations, including three different vehicles, with three different drivers, in three different environments, in which there are three different road surface types, in addition to variations in the conservation state and presence of anomalies and obstacles such as potholes and speed bumps. After data collection, these data were used in experiments to evaluate various aspects, such as the influence of the vehicle data collection point, the analysis domain, the model input features, and the data window. Afterwards we evaluated the learning and generalization capacity of the models for unknown contexts. In a third step, the data were used in three Deep Neural Network (DNN) models: LSTM-based, GRU-based, and CNN-based. Through a multi-aspect and multi-contextual analysis, we considered the CNN-based model as the best one, which obtained an average accuracy between the data collection placements of 94.27% for learning and 92.70% for validation, classifying the road surface between asphalt, cobblestone or dirt road segments.

关键词： Roads Sensors Data models Vehicles Sensor systems Deep learning Data collection

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Vspline 37

Vspline

引用

37th Annual Conference of the Association for computer Aided Design in Architecture: Disciplines and Disruption, ACADIA 2017

作者： Arnowitz, Ethan Morse, Christopher Greenberg, Donald P. Cornell University Program of Computer Graphics United States

ISBN: (纸本)9780692965061

Virtual reality provides a heightened sense of immersion and spatial awareness that provides a unique opportunity for designers to perceive and evaluate scale and space. At the same time, traditional sketches and small-size physical models provide tactile feedback that allow designers to create, comprehend, and explore complex geometric relationships. Through the development of vSpline, a modeling application for virtual reality, we explore the potential for design within a virtual spatial environment to blur the boundaries between digital and physical stages of design, and seek to combine the best of both virtual and analog worlds. By using spline-based closed meshes created directly in three-dimensional space, our software provides the capabilities to design, modify, and save the information in the virtual world and seamlessly convert the data to evaluate the printing of 3D physical models. We identify and discuss important questions that arise regarding relationships of perception of scale, digital-to-physical domains, and new methods of input and manipulation within a 3D im rsive space. © 2017 CURRAN-CONFERENCE. All rights reserved.

关键词： Virtual reality

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