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Author: Mayoore Selvarasa Jaiswal
Publisher:
ISBN:
Category :
Languages : en
Pages : 123
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Book Description
With the introduction of economical depth cameras, computer vision research has made a huge leap forward in 3D reconstruction and understanding. However, the quality of the depth images are limited: 1) depth images contain holes and random noise due to the characteristics of the cameras and the physical world, and 2) depth images have a lower spatial resolution. These challenges make 3D object reconstruction with a limited number of RGB-D frames a difficult task. In this dissertation, we propose a method to construct 3D object models with a limited number of RGB and depth frames. We developed a complete 3D object model construction process with automatic object segmentation, pairwise registration, global alignment, model denoising, and texturing, and studied the effects of these functions on the constructed 3D object models. We also developed a process for objective performance evaluation of the constructed 3D object models. High-quality depth images are paramount to create quality 3D object models. Many depth denoising methods blur object boundaries. Partial point clouds created from depth images denoised by these methods have artifacts that make them unsuitable for 3D object modeling. We propose a method to find the clean depth edge image using the noisy depth image and a color image, then use this clean depth edge image with the proposed edge and color aware adaptive trilateral filter to obtain denoised depth images. Finally, we propose to apply depth denoising and depth super-resolution in the 3D object modeling process. We preprocess depth images with the proposed depth denoising method and a state-of-the-art depth super-resolution method, then experiment the use of these preprocessed depth images under various conditions in the 3D object modeling process. We show that depth denoising and super-resolution can improve the quality of the 3D object models.
Author: Mayoore Selvarasa Jaiswal
Publisher:
ISBN:
Category :
Languages : en
Pages : 123
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Book Description
With the introduction of economical depth cameras, computer vision research has made a huge leap forward in 3D reconstruction and understanding. However, the quality of the depth images are limited: 1) depth images contain holes and random noise due to the characteristics of the cameras and the physical world, and 2) depth images have a lower spatial resolution. These challenges make 3D object reconstruction with a limited number of RGB-D frames a difficult task. In this dissertation, we propose a method to construct 3D object models with a limited number of RGB and depth frames. We developed a complete 3D object model construction process with automatic object segmentation, pairwise registration, global alignment, model denoising, and texturing, and studied the effects of these functions on the constructed 3D object models. We also developed a process for objective performance evaluation of the constructed 3D object models. High-quality depth images are paramount to create quality 3D object models. Many depth denoising methods blur object boundaries. Partial point clouds created from depth images denoised by these methods have artifacts that make them unsuitable for 3D object modeling. We propose a method to find the clean depth edge image using the noisy depth image and a color image, then use this clean depth edge image with the proposed edge and color aware adaptive trilateral filter to obtain denoised depth images. Finally, we propose to apply depth denoising and depth super-resolution in the 3D object modeling process. We preprocess depth images with the proposed depth denoising method and a state-of-the-art depth super-resolution method, then experiment the use of these preprocessed depth images under various conditions in the 3D object modeling process. We show that depth denoising and super-resolution can improve the quality of the 3D object models.
Author: Hannes Ovrén
Publisher: Linköping University Electronic Press
ISBN: 917685244X
Category :
Languages : en
Pages : 67
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Book Description
Using images to reconstruct the world in three dimensions is a classical computer vision task. Some examples of applications where this is useful are autonomous mapping and navigation, urban planning, and special effects in movies. One common approach to 3D reconstruction is ”structure from motion” where a scene is imaged multiple times from different positions, e.g. by moving the camera. However, in a twist of irony, many structure from motion methods work best when the camera is stationary while the image is captured. This is because the motion of the camera can cause distortions in the image that lead to worse image measurements, and thus a worse reconstruction. One such distortion common to all cameras is motion blur, while another is connected to the use of an electronic rolling shutter. Instead of capturing all pixels of the image at once, a camera with a rolling shutter captures the image row by row. If the camera is moving while the image is captured the rolling shutter causes non-rigid distortions in the image that, unless handled, can severely impact the reconstruction quality. This thesis studies methods to robustly perform 3D reconstruction in the case of a moving camera. To do so, the proposed methods make use of an inertial measurement unit (IMU). The IMU measures the angular velocities and linear accelerations of the camera, and these can be used to estimate the trajectory of the camera over time. Knowledge of the camera motion can then be used to correct for the distortions caused by the rolling shutter. Another benefit of an IMU is that it can provide measurements also in situations when a camera can not, e.g. because of excessive motion blur, or absence of scene structure. To use a camera together with an IMU, the camera-IMU system must be jointly calibrated. The relationship between their respective coordinate frames need to be established, and their timings need to be synchronized. This thesis shows how to automatically perform this calibration and synchronization, without requiring e.g. calibration objects or special motion patterns. In standard structure from motion, the camera trajectory is modeled as discrete poses, with one pose per image. Switching instead to a formulation with a continuous-time camera trajectory provides a natural way to handle rolling shutter distortions, and also to incorporate inertial measurements. To model the continuous-time trajectory, many authors have used splines. The ability for a spline-based trajectory to model the real motion depends on the density of its spline knots. Choosing a too smooth spline results in approximation errors. This thesis proposes a method to estimate the spline approximation error, and use it to better balance camera and IMU measurements, when used in a sensor fusion framework. Also proposed is a way to automatically decide how dense the spline needs to be to achieve a good reconstruction. Another approach to reconstruct a 3D scene is to use a camera that directly measures depth. Some depth cameras, like the well-known Microsoft Kinect, are susceptible to the same rolling shutter effects as normal cameras. This thesis quantifies the effect of the rolling shutter distortion on 3D reconstruction, depending on the amount of motion. It is also shown that a better 3D model is obtained if the depth images are corrected using inertial measurements. Att använda bilder för att återskapa världen omkring oss i tre dimensioner är ett klassiskt problem inom datorseende. Några exempel på användningsområden är inom navigering och kartering för autonoma system, stadsplanering och specialeffekter för film och spel. En vanlig metod för 3D-rekonstruktion är det som kallas ”struktur från rörelse”. Namnet kommer sig av att man avbildar (fotograferar) en miljö från flera olika platser, till exempel genom att flytta kameran. Det är därför något ironiskt att många struktur-från-rörelse-algoritmer får problem om kameran inte är stilla när bilderna tas, exempelvis genom att använda sig av ett stativ. Anledningen är att en kamera i rörelse ger upphov till störningar i bilden vilket ger sämre bildmätningar, och därmed en sämre 3D-rekonstruktion. Ett välkänt exempel är rörelseoskärpa, medan ett annat är kopplat till användandet av en elektronisk rullande slutare. I en kamera med rullande slutare avbildas inte alla pixlar i bilden samtidigt, utan istället rad för rad. Om kameran rör på sig medan bilden tas uppstår därför störningar i bilden som måste tas om hand om för att få en bra rekonstruktion. Den här avhandlingen berör robusta metoder för 3D-rekonstruktion med rörliga kameror. En röd tråd inom arbetet är användandet av en tröghetssensor (IMU). En IMU mäter vinkelhastigheter och accelerationer, och dessa mätningar kan användas för att bestämma hur kameran har rört sig över tid. Kunskap om kamerans rörelse ger möjlighet att korrigera för störningar på grund av den rullande slutaren. Ytterligare en fördel med en IMU är att den ger mätningar även i de fall då en kamera inte kan göra det. Exempel på sådana fall är vid extrem rörelseoskärpa, starkt motljus, eller om det saknas struktur i bilden. Om man vill använda en kamera tillsammans med en IMU så måste dessa kalibreras och synkroniseras: relationen mellan deras respektive koordinatsystem måste bestämmas, och de måste vara överens om vad klockan är. I den här avhandlingen presenteras en metod för att automatiskt kalibrera och synkronisera ett kamera-IMU-system utan krav på exempelvis kalibreringsobjekt eller speciella rörelsemönster. I klassisk struktur från rörelse representeras kamerans rörelse av att varje bild beskrivs med en kamera-pose. Om man istället representerar kamerarörelsen som en tidskontinuerlig trajektoria kan man på ett naturligt sätt hantera problematiken kring rullande slutare. Det gör det också enkelt att införa tröghetsmätningar från en IMU. En tidskontinuerlig kameratrajektoria kan skapas på flera sätt, men en vanlig metod är att använda sig av så kallade splines. Förmågan hos en spline att representera den faktiska kamerarörelsen beror på hur tätt dess knutar placeras. Den här avhandlingen presenterar en metod för att uppskatta det approximationsfel som uppkommer vid valet av en för gles spline. Det uppskattade approximationsfelet kan sedan användas för att balansera mätningar från kameran och IMU:n när dessa används för sensorfusion. Avhandlingen innehåller också en metod för att bestämma hur tät en spline behöver vara för att ge ett gott resultat. En annan metod för 3D-rekonstruktion är att använda en kamera som också mäter djup, eller avstånd. Vissa djupkameror, till exempel Microsoft Kinect, har samma problematik med rullande slutare som vanliga kameror. I den här avhandlingen visas hur den rullande slutaren i kombination med olika typer och storlekar av rörelser påverkar den återskapade 3D-modellen. Genom att använda tröghetsmätningar från en IMU kan djupbilderna korrigeras, vilket visar sig ge en bättre 3D-modell.
Author: Yong-Sheng Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Ioannis Kompatsiaris
Publisher: Springer
ISBN: 303005716X
Category : Computers
Languages : en
Pages : 719
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Book Description
The two-volume set LNCS 11295 and 11296 constitutes the thoroughly refereed proceedings of the 25th International Conference on MultiMedia Modeling, MMM 2019, held in Thessaloniki, Greece, in January 2019. Of the 172 submitted full papers, 49 were selected for oral presentation and 47 for poster presentation; in addition, 6 demonstration papers, 5 industry papers, 6 workshop papers, and 6 papers for the Video Browser Showdown 2019 were accepted. All papers presented were carefully reviewed and selected from 204 submissions.
Author: Jaydev P. Desai
Publisher: Springer
ISBN: 3319000659
Category : Technology & Engineering
Languages : en
Pages : 966
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Book Description
The International Symposium on Experimental Robotics (ISER) is a series of bi-annual meetings, which are organized, in a rotating fashion around North America, Europe and Asia/Oceania. The goal of ISER is to provide a forum for research in robotics that focuses on novelty of theoretical contributions validated by experimental results. The meetings are conceived to bring together, in a small group setting, researchers from around the world who are in the forefront of experimental robotics research. This unique reference presents the latest advances across the various fields of robotics, with ideas that are not only conceived conceptually but also explored experimentally. It collects robotics contributions on the current developments and new directions in the field of experimental robotics, which are based on the papers presented at the 13the ISER held in Québec City, Canada, at the Fairmont Le Château Frontenac, on June 18-21, 2012. This present thirteenth edition of Experimental Robotics edited by Jaydev P. Desai, Gregory Dudek, Oussama Khatib, and Vijay Kumar offers a collection of a broad range of topics in field and human-centered robotics.
Author: Laurent Amsaleg
Publisher: Springer
ISBN: 3319518119
Category : Computers
Languages : en
Pages : 759
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Book Description
The two-volume set LNCS 10132 and 10133 constitutes the thoroughly refereed proceedings of the 23rd International Conference on Multimedia Modeling, MMM 2017, held in Reykjavik, Iceland, in January 2017. Of the 149 full papers submitted, 36 were selected for oral presentation and 33 for poster presentation; of the 34 special session papers submitted, 24 were selected for oral presentation and 2 for poster presentation; in addition, 5 demonstrations were accepted from 8 submissions, and all 7 submissions to VBS 2017. All papers presented were carefully reviewed and selected from 198 submissions. MMM is a leading international conference for researchers and industry practitioners for sharing new ideas, original research results and practical development experiences from all MMM related areas, broadly falling into three categories: multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.
Author: Newton Lee
Publisher: Springer Nature
ISBN: 3031231619
Category : Computers
Languages : en
Pages : 2150
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Book Description
Encyclopedia of Computer Graphics and Games (ECGG) is a unique reference resource tailored to meet the needs of research and applications for industry professionals and academic communities worldwide. The ECGG covers the history, technologies, and trends of computer graphics and games. Editor Newton Lee, Institute for Education, Research, and Scholarships, Los Angeles, CA, USA Academic Co-Chairs Shlomo Dubnov, Department of Music and Computer Science and Engineering, University of California San Diego, San Diego, CA, USA Patrick C. K. Hung, University of Ontario Institute of Technology, Oshawa, ON, Canada Jaci Lee Lederman, Vincennes University, Vincennes, IN, USA Industry Co-Chairs Shuichi Kurabayashi, Cygames, Inc. & Keio University, Kanagawa, Japan Xiaomao Wu, Gritworld GmbH, Frankfurt am Main, Hessen, Germany Editorial Board Members Leigh Achterbosch, School of Science, Engineering, IT and Physical Sciences, Federation University Australia Mt Helen, Ballarat, VIC, Australia Ramazan S. Aygun, Department of Computer Science, Kennesaw State University, Marietta, GA, USA Barbaros Bostan, BUG Game Lab, Bahçeşehir University (BAU), Istanbul, Turkey Anthony L. Brooks, Aalborg University, Aalborg, Denmark Guven Catak, BUG Game Lab, Bahçeşehir University (BAU), Istanbul, Turkey Alvin Kok Chuen Chan, Cambridge Corporate University, Lucerne, Switzerland Anirban Chowdhury, Department of User Experience and Interaction Design, School of Design (SoD), University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India Saverio Debernardis, Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Bari, Italy Abdennour El Rhalibi, Liverpool John Moores University, Liverpool, UK Stefano Ferretti, Department of Computer Science and Engineering, University of Bologna, Bologna, Italy Han Hu, School of Information and Electronics, Beijing Institute of Technology, Beijing, China Ms. Susan Johnston, Select Services Films Inc., Los Angeles, CA, USA Chris Joslin, Carleton University, Ottawa, Canada Sicilia Ferreira Judice, Department of Computer Science, University of Calgary, Calgary, Canada Hoshang Kolivand, Department Computer Science, Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, UK Dario Maggiorini, Department of Computer Science, University of Milan, Milan, Italy Tim McGraw, Purdue University, West Lafayette, IN, USA George Papagiannakis, ORamaVR S.A., Heraklion, Greece; FORTH-ICS, Heraklion Greece University of Crete, Heraklion, Greece Florian Richoux, Nantes Atlantic Computer Science Laboratory (LINA), Université de Nantes, Nantes, France Andrea Sanna, Dipartimento di Automatica e Informatica, Politecnico di Torino, Turin, Italy Yann Savoye, Institut fur Informatik, Innsbruck University, Innsbruck, Austria Sercan Şengün, Wonsook Kim School of Art, Illinois State University, Normal, IL, USA Ruck Thawonmas, Ritsumeikan University, Shiga, Japan Vinesh Thiruchelvam, Asia Pacific University of Technology & Innovation, Kuala Lumpur, Malaysia Rojin Vishkaie, Amazon, Seattle, WA, USA Duncan A. H. Williams, Digital Creativity Labs, Department of Computer Science, University of York, York, UK Sai-Keung Wong, National Chiao Tung University, Hsinchu, Taiwan Editorial Board Intern Sam Romershausen, Vincennes University, Vincennes, IN, USA
Author: Gang Hua
Publisher: Springer
ISBN: 3319494090
Category : Computers
Languages : en
Pages : 938
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Book Description
The three-volume set LNCS 9913, LNCS 9914, and LNCS 9915 comprises the refereed proceedings of the Workshops that took place in conjunction with the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The three-volume set LNCS 9913, LNCS 9914, and LNCS 9915 comprises the refereed proceedings of the Workshops that took place in conjunction with the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. 27 workshops from 44 workshops proposals were selected for inclusion in the proceedings. These address the following themes: Datasets and Performance Analysis in Early Vision; Visual Analysis of Sketches; Biological and Artificial Vision; Brave New Ideas for Motion Representations; Joint ImageNet and MS COCO Visual Recognition Challenge; Geometry Meets Deep Learning; Action and Anticipation for Visual Learning; Computer Vision for Road Scene Understanding and Autonomous Driving; Challenge on Automatic Personality Analysis; BioImage Computing; Benchmarking Multi-Target Tracking: MOTChallenge; Assistive Computer Vision and Robotics; Transferring and Adapting Source Knowledge in Computer Vision; Recovering 6D Object Pose; Robust Reading; 3D Face Alignment in the Wild and Challenge; Egocentric Perception, Interaction and Computing; Local Features: State of the Art, Open Problems and Performance Evaluation; Crowd Understanding; Video Segmentation; The Visual Object Tracking Challenge Workshop; Web-scale Vision and Social Media; Computer Vision for Audio-visual Media; Computer VISion for ART Analysis; Virtual/Augmented Reality for Visual Artificial Intelligence; Joint Workshop on Storytelling with Images and Videos and Large Scale Movie Description and Understanding Challenge.
Author: Richard Szeliski
Publisher: Springer Nature
ISBN: 3030343723
Category : Computers
Languages : en
Pages : 925
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Book Description
Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles. Topics and features: Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses Incorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented reality Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Author: David S. Wettergreen
Publisher: Springer
ISBN: 3319277022
Category : Technology & Engineering
Languages : en
Pages : 646
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Book Description
This book contains the proceedings of the 10th FSR, (Field and Service Robotics) which is the leading single-track conference on applications of robotics in challenging environments. The 10th FSR was held in Toronto, Canada from 23-26 June 2015. The book contains 42 full-length, peer-reviewed papers organized into a variety of topics: Aquatic, Vision, Planetary, Aerial, Underground, and Systems. The goal of the book and the conference is to report and encourage the development and experimental evaluation of field and service robots, and to generate a vibrant exchange and discussion in the community. Field robots are non-factory robots, typically mobile, that operate in complex and dynamic environments: on the ground (Earth or other planets), under the ground, underwater, in the air or in space. Service robots are those that work closely with humans to help them with their lives. The first FSR was held in Canberra, Australia, in 1997. Since that first meeting, FSR has been held roughly every two years, cycling through Asia, Americas, Europe.
